Print cartridge having internal tubular ink reservoir core

ABSTRACT

A printing cartridge includes a roll of print media; a tubular former around which the roll of print media is wound, the tubular former being internally separated into two or more sections along a longitudinal axis of the tubular former and adapted to store supplies of fluid therein; a casing comprising a pair of molded covers, the pair of molded covers being configured to releasably fasten together to encase the roll of print media; and an ink collar for sealing an end of the tubular former, the ink collar defining two or more slits adapted to receive therethrough fluid communication pins, whereby access to the supplies of fluid in the tubular former is effected.

CROSS-REFERENCE TO RELATED APPLICATION

This Application is Continuation Application of U.S. application Ser.No. 12/433,882 filed on Apr. 30, 2009, which is Continuation Applicationof U.S. application Ser. No. 11/740,287 filed Apr. 25, 2007, now issuedU.S. Pat. No. 7,575,313, which is a continuation of U.S. applicationSer. No. 10/485,739 filed on Feb. 4, 2004, now issued U.S. Pat. No.7,234,801, which is a 371 of PCT Application No. PCT/AU02/00921, filedon Jul. 9, 2002, which is a Continuation Application of U.S. applicationSer. No. 09/922,158, filed Aug. 6, 2001 now issued as U.S. Pat. No.7,044,589 all of which are herein incorporated by reference.

FIELD OF THE INVENTION

The present invention relates to the field of printer technology anddiscloses a printing cartridge for use in an image printer or the like.In particular, the present invention discloses a printing cartridge,which incorporates barcode identification.

BACKGROUND OF THE INVENTION

Recently, digital printing technology has been proposed as a suitablereplacement for traditional camera and photographic film techniques. Thetraditional film and photographic techniques rely upon a film rollhaving a number of pre-formatted negatives which are drawn past alensing system and onto which is imaged a negative of a image taken bythe lensing system. Upon the completion of a film roll, the film isrewound into its container and forwarded to a processing shop forprocessing and development of the negatives so as to produce acorresponding positive set of photos.

Unfortunately, such a system has a number of significant drawbacks.Firstly, the chemicals utilized are obviously very sensitive to lightand any light impinging upon the film roll will lead to exposure of thefilm. They are therefore required to operate in a light sensitiveenvironment where the light imaging is totally controlled. This resultsin onerous engineering requirements leading to increased expense.Further, film processing techniques require the utilizing of a“negative” and its subsequent processing onto a “positive” film paperthrough the utilization of processing chemicals and complex silverhalide processing etc. This is generally unduly cumbersome, complex andexpensive. Further, such a system through its popularity has lead to thestandardization on certain size film formats and generally minimalflexibility is possible with the aforementioned techniques.

Recently, all digital cameras have been introduced. These camera devicesnormally utilize a charge coupled device (CCD) or other form ofphotosensor connected to a processing chip which in turn is connected toand controls a media storage device which can take the form of adetachable magnetic card. In this type of device, the image is capturedby the CCD and stored on the magnetic storage device. At some latertime, the image or images that have been captured are down loaded to acomputer device and printed out for viewing. The digital camera has thedisadvantage that access to images is non-immediate and the further postprocessing step of loading onto a computer system is required, thefurther post processing often being a hindrance to ready and expedientuse.

Therefore, there remains a general need for an improved form of camerapicture image production apparatus which is convenient, simple andeffective in operation. Further, there also remains a need for a simpleform of portable, immediate print media on which images can beeffectively reproduced.

In the parent application, there is disclosed the use of anauthentication chip to provide information in connection with the printmedia and the media colorant that is supplied with the cartridge.

The Applicant has identified that it would be highly desirable toprovide a means whereby information concerning one or both of the mediaand the media colorant could be supplied together with the cartridge.The reason for this is that such information could be used, in asuitable form, by a processor of such a device to enhance operation of aprinting mechanism. It will be appreciated that printing mechanisms needto operate differently with different types of media and media colorant.It follows that it would be useful to supply information concerningmedia and media colorant to a controller of the printing mechanism sothat operation of the printing mechanism could be automatically adjustedto suit the particular media and media colorant.

With suitable encryption techniques, this could be used to inhibitafter-market refilling. As is well known in the field of printingtechnology, such after-market refilling has become a cause forsubstantial concern in the printing industry.

SUMMARY OF THE INVENTION

According to an aspect of the present disclosure, a printing cartridgecomprises a roll of print media; a tubular former around which the rollof print media is wound, the tubular former being internally separatedinto two or more sections along a longitudinal axis of the tubularformer and adapted to store supplies of fluid therein; a casingcomprising a pair of molded covers, the pair of molded covers beingconfigured to releasably fasten together to encase the roll of printmedia; and an ink collar for sealing an end of the tubular former, theink collar defining Two or more slits adapted to receive therethroughfluid communication pins, whereby access to the supplies of fluid in thetubular former is effected.

BRIEF DESCRIPTION OF THE DRAWINGS

Notwithstanding any other forms, which may fall within the scope of thepresent invention, preferred forms of the invention will now bedescribed, by way of example only, with reference to the accompanyingdrawings in which:

FIG. 1 illustrates an Artcam device constructed in accordance with thepreferred embodiment;

FIG. 2 is a schematic block diagram of the main Artcam electroniccomponents;

FIG. 2A is a schematic block diagram of the main Artcam components,including a barcode scanner;

FIG. 3 is a schematic block diagram of the Artcam Central Processor;

FIG. 3( a) illustrates the VLIW Vector Processor in more detail;

FIG. 3A is a schematic block diagram of the Artcam Central Processorincorporating a barcode reader interface;

FIG. 4 illustrates the Processing Unit in more detail;

FIG. 5 illustrates the ALU 188 in more detail;

FIG. 6 illustrates the In block in more detail;

FIG. 7 illustrates the Out block in more detail;

FIG. 8 illustrates the Registers block in more detail;

FIG. 9 illustrates the Crossbar1 in more detail;

FIG. 10 illustrates the Crossbar2 in more detail;

FIG. 11 illustrates the read process block in more detail;

FIG. 12 illustrates the read process block in more detail;

FIG. 13 illustrates the barrel shifter block in more detail;

FIG. 14 illustrates the adder/logic block in more detail;

FIG. 15 illustrates the multiply block in more detail;

FIG. 16 illustrates the I/O address generator block in more detail;

FIG. 17 illustrates a pixel storage format;

FIG. 18 illustrates a sequential read iterator process;

FIG. 19 illustrates a box read iterator process;

FIG. 20 illustrates a box write iterator process;

FIG. 21 illustrates the vertical strip read/write iterator process;

FIG. 22 illustrates the vertical strip read/write iterator process;

FIG. 23 illustrates the generate sequential process;

FIG. 24 illustrates the generate sequential process;

FIG. 25 illustrates the generate vertical strip process;

FIG. 26 illustrates the generate vertical strip process;

FIG. 27 illustrates a pixel data configuration;

FIG. 28 illustrates a pixel processing process;

FIG. 29 illustrates a schematic block diagram of the display controller;

FIG. 30 illustrates the CCD image organization;

FIG. 31 illustrates the storage format for a logical image;

FIG. 32 illustrates the internal image memory storage format;

FIG. 33 illustrates the image pyramid storage format;

FIG. 34 illustrates a time line of the process of sampling an Artcard;

FIG. 35 illustrates the super sampling process;

FIG. 36 illustrates the process of reading a rotated Artcard;

FIG. 37 illustrates a flow chart of the steps necessary to decode anArtcard;

FIG. 38 illustrates an enlargement of the left hand corner of a singleArtcard;

FIG. 39 illustrates a single target for detection;

FIG. 40 illustrates the method utilised to detect targets;

FIG. 41 illustrates the method of calculating the distance between twotargets;

FIG. 42 illustrates the process of centroid drift;

FIG. 43 shows one form of centroid lookup table;

FIG. 44 illustrates the centroid updating process;

FIG. 45 illustrates a delta processing lookup table utilised in thepreferred embodiment;

FIG. 46 illustrates the process of unscrambling Artcard data;

FIG. 47 illustrates a magnified view of a series of dots;

FIG. 48 illustrates the data surface of a dot card;

FIG. 49 illustrates schematically the layout of a single datablock;

FIG. 50 illustrates a single datablock;

FIG. 51 and FIG. 52 illustrate magnified views of portions of thedatablock of FIG. 50;

FIG. 53 illustrates a single target structure;

FIG. 54 illustrates the target structure of a datablock;

FIG. 55 illustrates the positional relationship of targets relative toborder clocking regions of a data region;

FIG. 56 illustrates the orientation columns of a datablock;

FIG. 57 illustrates the array of dots of a datablock;

FIG. 58 illustrates schematically the structure of data for Reed-Solomonencoding;

FIG. 59 illustrates an example Reed-Solomon encoding;

FIG. 60 illustrates the Reed-Solomon encoding process;

FIG. 61 illustrates the layout of encoded data within a datablock;

FIG. 62 illustrates the sampling process in sampling an alternativeArtcard;

FIG. 63 illustrates, in exaggerated form, an example of sampling arotated alternative Artcard;

FIG. 64 illustrates the scanning process;

FIG. 65 illustrates the likely scanning distribution of the scanningprocess;

FIG. 66 illustrates the relationship between probability of symbolerrors and Reed-Solomon block errors;

FIG. 67 illustrates a flow chart of the decoding process;

FIG. 68 illustrates a process utilization diagram of the decodingprocess;

FIG. 69 illustrates the dataflow steps in decoding;

FIG. 70 illustrates the reading process in more detail;

FIG. 71 illustrates the process of detection of the start of analternative Artcard in more detail;

FIG. 72 illustrates the extraction of bit data process in more detail;

FIG. 73 illustrates the segmentation process utilized in the decodingprocess;

FIG. 74 illustrates the decoding process of finding targets in moredetail;

FIG. 75 illustrates the data structures utilized in locating targets;

FIG. 76 illustrates the Lancos 3 function structure;

FIG. 77 illustrates an enlarged portion of a datablock illustrating theclockmark and border region;

FIG. 78 illustrates the processing steps in decoding a bit image;

FIG. 79 illustrates the dataflow steps in decoding a bit image;

FIG. 80 illustrates the descrambling process of the preferredembodiment;

FIG. 81 illustrates one form of implementation of the convolver;

FIG. 82 illustrates a convolution process;

FIG. 83 illustrates the compositing process;

FIG. 84 illustrates the regular compositing process in more detail;

FIG. 85 illustrates the process of warping using a warp map;

FIG. 86 illustrates the warping bi-linear interpolation process;

FIG. 87 illustrates the process of span calculation;

FIG. 88 illustrates the basic span calculation process;

FIG. 89 illustrates one form of detail implementation of the spancalculation process;

FIG. 90 illustrates the process of reading image pyramid levels;

FIG. 91 illustrates using the pyramid table for bilinear interpolation;

FIG. 92 illustrates the histogram collection process;

FIG. 93 illustrates the color transform process;

FIG. 94 illustrates the color conversion process;

FIG. 95 illustrates the color space conversion process in more detail;

FIG. 96 illustrates the process of calculating an input coordinate;

FIG. 97 illustrates the process of compositing with feedback;

FIG. 98 illustrates the generalized scaling process;

FIG. 99 illustrates the scale in X scaling process;

FIG. 100 illustrates the scale in Y scaling process;

FIG. 101 illustrates the tessellation process;

FIG. 102 illustrates the sub-pixel translation process;

FIG. 103 illustrates the compositing process;

FIG. 104 illustrates the process of compositing with feedback;

FIG. 105 illustrates the process of tiling with color from the inputimage;

FIG. 106 illustrates the process of tiling with feedback;

FIG. 107 illustrates the process of tiling with texture replacement;

FIG. 108 illustrates the process of tiling with color from the inputimage;

FIG. 108 illustrates the process of tiling with color from the inputimage;

FIG. 109 illustrates the process of applying a texture without feedback;

FIG. 110 illustrates the process of applying a texture with feedback;

FIG. 111 illustrates the process of rotation of CCD pixels;

FIG. 112 illustrates the process of interpolation of Green subpixels;

FIG. 113 illustrates the process of interpolation of Blue subpixels;

FIG. 114 illustrates the process of interpolation of Red subpixels;

FIG. 115 illustrates the process of CCD pixel interpolation with 0degree rotation for odd pixel lines;

FIG. 116 illustrates the process of CCD pixel interpolation with 0degree rotation for even pixel lines;

FIG. 117 illustrates the process of color conversion to Lab color space;

FIG. 118 illustrates the process of calculation of 1/√X;

FIG. 119 illustrates the implementation of the calculation of 1/√X inmore detail;

FIG. 120 illustrates the process of Normal calculation with a bump map;

FIG. 121 illustrates the process of illumination calculation with a bumpmap;

FIG. 122 illustrates the process of illumination calculation with a bumpmap in more detail;

FIG. 123 illustrates the process of calculation of L using a directionallight;

FIG. 124 illustrates the process of calculation of L using a Omni lightsand spotlights;

FIG. 125 illustrates one form of implementation of calculation of Lusing a Omni lights and spotlights;

FIG. 126 illustrates the process of calculating the N·L dot product;

FIG. 127 illustrates the process of calculating the N·L dot product inmore detail;

FIG. 128 illustrates the process of calculating the R·V dot product;

FIG. 129 illustrates the process of calculating the R·V dot product inmore detail;

FIG. 130 illustrates the attenuation calculation inputs and outputs;

FIG. 131 illustrates an actual implementation of attenuationcalculation;

FIG. 132 illustrates a graph of the cone factor;

FIG. 133 illustrates the process of penumbra calculation;

FIG. 134 illustrates the angles utilised in penumbra calculation;

FIG. 135 illustrates the inputs and outputs to penumbra calculation;

FIG. 136 illustrates an actual implementation of penumbra calculation;

FIG. 137 illustrates the inputs and outputs to ambient calculation;

FIG. 138 illustrates an actual implementation of ambient calculation;

FIG. 139 illustrates an actual implementation of diffuse calculation;

FIG. 140 illustrates the inputs and outputs to a diffuse calculation;

FIG. 141 illustrates an actual implementation of a diffuse calculation;

FIG. 142 illustrates the inputs and outputs to a specular calculation;

FIG. 143 illustrates an actual implementation of a specular calculation;

FIG. 144 illustrates the inputs and outputs to a specular calculation;

FIG. 145 illustrates an actual implementation of a specular calculation;

FIG. 146 illustrates an actual implementation of an ambient onlycalculation;

FIG. 147 illustrates the process overview of light calculation;

FIG. 148 illustrates an example illumination calculation for a singleinfinite light source;

FIG. 149 illustrates an example illumination calculation for an Omnilight source without a bump map;

FIG. 150 illustrates an example illumination calculation for an Omnilight source with a bump map;

FIG. 151 illustrates an example illumination calculation for a Spotlightlight source without a bump map;

FIG. 152 illustrates the process of applying a single Spotlight onto animage with an associated bump-map;

FIG. 153 illustrates the logical layout of a single printhead;

FIG. 154 illustrates the structure of the printhead interface;

FIG. 155 illustrates the process of rotation of a Lab image;

FIG. 156 illustrates the format of a pixel of the printed image;

FIG. 157 illustrates the dithering process;

FIG. 158 illustrates the process of generating an 8-bit dot output;

FIG. 159 illustrates a perspective view of the card reader;

FIG. 160 illustrates an exploded perspective of a card reader;

FIG. 161 illustrates a close up view of the Artcard reader;

FIG. 162 illustrates a perspective view of the print roll and printhead;

FIG. 163 illustrates a first exploded perspective view of the printroll;

FIG. 164 illustrates a second exploded perspective view of the printroll;

FIG. 164A illustrates a three dimensional view of another embodiment ofthe print roll and print head in the form of a printing cartridge alsoin accordance with the invention;

FIG. 164B illustrates a three dimensional, sectional view of the printcartridge of FIG. 164A;

FIG. 164C shows a three dimensional, exploded view of the printcartridge of FIG. 164A;

FIG. 164D shows a three dimensional, exploded view of an ink cartridgeforming part of the print cartridge of FIG. 164A;

FIG. 164E shows a three dimensional view of an air filter of the printcartridge of FIG. 164A;

FIG. 164F shows a three dimensional view of a further embodiment of aprint cartridge incorporating a barcode and in combination with anArtcam device having a barcode reader;

FIG. 164G shows a simple diagram indicating operation of the barcodereader and a lookup algorithm carried by a processor of the Artcamdevice;

FIG. 165 illustrates the print roll authentication chip;

FIG. 166 illustrates an enlarged view of the print roll authenticationchip;

FIG. 167 illustrates a single authentication chip data protocol;

FIG. 168 illustrates a dual authentication chip data protocol;

FIG. 169 illustrates a first presence only protocol;

FIG. 170 illustrates a second presence only protocol;

FIG. 171 illustrates a third data protocol;

FIG. 172 illustrates a fourth data protocol;

FIG. 173 is a schematic block diagram of a maximal period LFSR;

FIG. 174 is a schematic block diagram of a clock limiting filter;

FIG. 175 is a schematic block diagram of the tamper detection lines;

FIG. 176 illustrates an oversized nMOS transistor;

FIG. 177 illustrates the taking of multiple XORs from the Tamper DetectLine

FIG. 178 illustrates how the Tamper Lines cover the noise generatorcircuitry;

FIG. 179 illustrates the normal form of FET implementation;

FIG. 180 illustrates the modified form of FET implementation of thepreferred embodiment;

FIG. 181 illustrates a schematic block diagram of the authenticationchip;

FIG. 182 illustrates an example memory map;

FIG. 183 illustrates an example of the constants memory map;

FIG. 184 illustrates an example of the RAM memory map;

FIG. 185 illustrates an example of the Flash memory variables memorymap;

FIG. 186 illustrates an example of the Flash memory program memory map;

FIG. 187 shows the data flow and relationship between components of theState Machine;

FIG. 188 shows the data flow and relationship between components of theI/O Unit.

FIG. 189 illustrates a schematic block diagram of the Arithmetic LogicUnit;

FIG. 190 illustrates a schematic block diagram of the RPL unit;

FIG. 191 illustrates a schematic block diagram of the ROR block of theALU;

FIG. 192 is a block diagram of the Program Counter Unit;

FIG. 193 is a block diagram of the Memory Unit;

FIG. 194 shows a schematic block diagram for the Address Generator Unit;

FIG. 195 shows a schematic block diagram for the JSIGEN Unit;

FIG. 196 shows a schematic block diagram for the JSRGEN Unit.

FIG. 197 shows a schematic block diagram for the DBRGEN Unit;

FIG. 198 shows a schematic block diagram for the LDKGEN Unit;

FIG. 199 shows a schematic block diagram for the RPLGEN Unit;

FIG. 200 shows a schematic block diagram for the VARGEN Unit.

FIG. 201 shows a schematic block diagram for the CLRGEN Unit.

FIG. 202 shows a schematic block diagram for the BITGEN Unit.

FIG. 203 sets out the information stored on the print rollauthentication chip;

FIG. 204 illustrates the data stored within the Artcam authorizationchip;

FIG. 205 illustrates the process of print head pulse characterization;

FIG. 206 is an exploded perspective, in section, of the print head inksupply mechanism;

FIG. 207 is a bottom perspective of the ink head supply unit;

FIG. 208 is a bottom side sectional view of the ink head supply unit;

FIG. 209 is a top perspective of the ink head supply unit;

FIG. 210 is a top side sectional view of the ink head supply unit;

FIG. 211 illustrates a perspective view of a small portion of the printhead;

FIG. 212 illustrates is an exploded perspective of the print head unit;

FIG. 213 illustrates a top side perspective view of the internalportions of an Artcam camera, showing the parts flattened out;

FIG. 214 illustrates a bottom side perspective view of the internalportions of an Artcam camera, showing the parts flattened out;

FIG. 215 illustrates a first top side perspective view of the internalportions of an Artcam camera, showing the parts as encased in an Artcam;

FIG. 216 illustrates a second top side perspective view of the internalportions of an Artcam camera, showing the parts as encased in an Artcam;

FIG. 217 illustrates a second top side perspective view of the internalportions of an Artcam camera, showing the parts as encased in an Artcam;

FIG. 218 illustrates the backing portion of a postcard print roll;

FIG. 219 illustrates the corresponding front image on the postcard printroll after printing out images;

FIG. 220 illustrates a form of print roll ready for purchase by aconsumer;

FIG. 221 illustrates a layout of the software/hardware modules of theoverall Artcam application;

FIG. 222 illustrates a layout of the software/hardware modules of theCamera Manager;

FIG. 223 illustrates a layout of the software/hardware modules of theImage Processing Manager;

FIG. 224 illustrates a layout of the software/hardware modules of thePrinter Manager;

FIG. 225 illustrates a layout of the software/hardware modules of theImage Processing Manager;

FIG. 226 illustrates a layout of the software/hardware modules of theFile Manager;

FIG. 227 illustrates a perspective view, partly in section, of analternative form of printroll;

FIG. 228 is a left side exploded perspective view of the print roll ofFIG. 227;

FIG. 229 is a right side exploded perspective view of a singleprintroll;

FIG. 230 is an exploded perspective view, partly in section, of the coreportion of the printroll; and

FIG. 231 is a second exploded perspective view of the core portion ofthe printroll.

DESCRIPTION OF PREFERRED AND OTHER EMBODIMENTS

The digital image processing camera system constructed in accordancewith the preferred embodiment is as illustrated in FIG. 1. The cameraunit 1 includes means for the insertion of an integral print roll (notshown). The camera unit 1 can include an area image sensor 2 whichsensors an image 3 for captured by the camera. Optionally, the secondarea image sensor can be provided to also image the scene 3 and tooptionally provide for the production of stereographic output effects.The camera 1 can include an optional color display 5 for the display ofthe image being sensed by the sensor 2. When a simple image is beingdisplayed on the display 5, the button 6 can be depressed resulting inthe printed image 8 being output by the camera unit 1. A series ofcards, herein after known as “Artcards” 9 contain, on one surface,encoded information and on the other surface, contain an image distortedby the particular effect produced by the Artcard 9. The Artcard 9 isinserted in an Artcard reader 10 in the side of camera 1 and, uponinsertion, results in output image 8 being distorted in the same manneras the distortion appearing on the surface of Artcard 9. Hence, by meansof this simple user interface a user wishing to produce a particulareffect can insert one of many Artcards 9 into the Artcard reader 10 andutilize button 19 to take a picture of the image 3 resulting in acorresponding distorted output image 8.

The camera unit 1 can also include a number of other control button 13,14 in addition to a simple LCD output display 15 for the display ofinformative information including the number of printouts left on theinternal print roll on the camera unit. Additionally, different outputformats can be controlled by CHP switch 17.

Turning now to FIG. 2, there is illustrated a schematic view of theinternal hardware of the camera unit 1. The internal hardware is basedaround an Artcam central processor unit (ACP) 31.

Artcam Central Processor 31

The Artcam central processor 31 provides many functions, which form the‘heart’ of the system. The ACP 31 is preferably implemented as acomplex, high speed, CMOS system on-a-chip. Utilising standard celldesign with some full custom regions is recommended. Fabrication on a0.25 micron CMOS process will provide the density and speed required,along with a reasonably small die area.

The functions provided by the ACP 31 include:

1. Control and digitization of the area image sensor 2. A 3Dstereoscopic version of the ACP requires two area image sensorinterfaces with a second optional image sensor 4 being provided forstereoscopic effects.

2. Area image sensor compensation, reformatting, and image enhancement.

3. Memory interface and management to a memory store 33.

4. Interface, control, and analog to digital conversion of an Artcardreader linear image sensor 34 which is provided for the reading of datafrom the Artcards 9.

5. Extraction of the raw Artcard data from the digitized and encodedArtcard image.

6. Reed-Solomon error detection and correction of the Artcard encodeddata. The encoded surface of the Artcard 9 includes information on howto process an image to produce the effects displayed on the imagedistorted surface of the Artcard 9. This information is in the form of ascript, hereinafter known as a “Vark script”. The Vark script isutilised by an interpreter running within the ACP 31 to produce thedesired effect.

7. Interpretation of the Vark script on the Artcard 9.

8. Performing image processing operations as specified by the Varkscript.

9. Controlling various motors for the paper transport 36, zoom lens 38,autofocus 39 and Artcard driver 37.

10. Controlling a guillotine actuator 40 for the operation of aguillotine 41 for the cutting of photographs 8 from print roll 42.

11. Half-toning of the image data for printing.

12. Providing the print data to a print-head 44 at the appropriatetimes.

13. Controlling the print head 44.

14. Controlling the ink pressure feed to print-head 44.

15. Controlling optional flash unit 56.

16. Reading and acting on various sensors in the camera, includingcamera orientation sensor 46, autofocus 47 and Artcard insertion sensor49.

17. Reading and acting on the user interface buttons 6, 13, 14.

18. Controlling the status display 15.

19. Providing viewfinder and preview images to the color display 5.

20. Control of the system power consumption, including the ACP powerconsumption via power management circuit 51.

21. Providing external communications 52 to general purpose computers(using part USB).

22. Reading and storing information in a printing roll authenticationchip 53.

23. Reading and storing information in a camera authentication chip 54.

24. Communicating with an optional mini-keyboard 57 for textmodification.

Quartz Crystal 58

A quartz crystal 58 is used as a frequency reference for the systemclock. As the system clock is very high, the ACP 31 includes a phaselocked loop clock circuit to increase the frequency derived from thecrystal 58.

Image Sensing Area Image Sensor 2

The area image sensor 2 converts an image through its lens into anelectrical signal. It can either be a charge coupled device (CCD) or anactive pixel sensor (APS) CMOS image sector. At present, available CCD'snormally have a higher image quality, however, there is currently muchdevelopment occurring in CMOS imagers. CMOS imagers are eventuallyexpected to be substantially cheaper than CCD's have smaller pixelareas, and be able to incorporate drive circuitry and signal processing.They can also be made in CMOS fabs, which are transitioning to 12″wafers. CCD's are usually built in 6″ wafer fabs, and economics may notallow a conversion to 12″ fabs. Therefore, the difference in fabricationcost between CCD's and CMOS imagers is likely to increase, progressivelyfavoring CMOS imagers. However, at present, a CCD is probably the bestoption.

The Artcam unit will produce suitable results with a 1,500×1,000 areaimage sensor. However, smaller sensors, such as 750×500, will beadequate for many markets. The Artcam is less sensitive to image sensorresolution than are conventional digital cameras. This is because manyof the styles contained on Artcards 9 process the image in such a way asto obscure the lack of resolution. For example, if the image isdistorted to simulate the effect of being converted to animpressionistic painting, low source image resolution can be used withminimal effect. Further examples for which low resolution input imageswill typically not be noticed include image warps which produce highdistorted images, multiple miniature copies of the of the image (e.g.passport photos), textural processing such as bump mapping for a baserelief metal look, and photo-compositing into structured scenes.

This tolerance of low resolution image sensors may be a significantfactor in reducing the manufacturing cost of an Artcam unit 1 camera. AnArtcam with a low cost 750×500 image sensor will often produce superiorresults to a conventional digital camera with a much more expensive1,500×1,000 image sensor.

Optional Stereoscopic 3D Image Sensor 4

The 3D versions of the Artcam unit 1 have an additional image sensor 4,for stereoscopic operation. This image sensor is identical to the mainimage sensor. The circuitry to drive the optional image sensor may beincluded as a standard part of the ACP chip 31 to reduce incrementaldesign cost. Alternatively, a separate 3D Artcam ACP can be designed.This option will reduce the manufacturing cost of a mainstream singlesensor Artcam.

Print Roll Authentication Chip 53

A small chip 53 is included in each print roll 42. This chip replacedthe functions of the bar code, optical sensor and wheel, and ISO/ASAsensor on other forms of camera film units such as Advanced PhotoSystems film cartridges.

The authentication chip also provides other features:

1. The storage of data rather than that, which is mechanically andoptically, sensed from APS rolls

2. A remaining media length indication, accurate to high resolution.

3. Authentication Information to prevent inferior clone print rollcopies.

The authentication chip 53 contains 1024 bits of Flash memory, of which128 bits is an authentication key, and 512 bits is the authenticationinformation. Also included is an encryption circuit to ensure that theauthentication key cannot be accessed directly.

Print Head 44

The Artcam unit 1 can utilize any color print technology, which is smallenough, low enough power, fast enough, high enough quality, and lowenough cost, and is compatible with the print roll. Relevant printheadswill be specifically discussed hereinafter.

The specifications of the ink jet head are:

Image type Bi-level, dithered Color CMY Process Color Resolution 1600dpi Print head length ‘Page-width’ (100 mm) Print speed 2 seconds perphoto

Optional Ink Pressure Controller (Not Shown)

The function of the ink pressure controller depends upon the type of inkjet print head 44 incorporated in the Artcam. For some types of ink jet,the use of an ink pressure controller can be eliminated, as the inkpressure is simply atmospheric pressure. Other types of print headrequire a regulated positive ink pressure. In this case, the in pressurecontroller consists of a pump and pressure transducer.

Other print heads may require an ultrasonic transducer to cause regularoscillations in the ink pressure, typically at frequencies around 100KHz. In the case, the ACP 31 controls the frequency phase and amplitudeof these oscillations.

Paper Transport Motor 36

The paper transport motor 36 moves the paper from within the print roll42 past the print head at a relatively constant rate. The motor 36 is aminiature motor geared down to an appropriate speed to drive rollers,which move the paper. A high quality motor and mechanical gears arerequired to achieve high image quality, as mechanical rumble or othervibrations will affect the printed dot row spacing.

Paper Transport Motor Driver 60

The motor driver 60 is a small circuit, which amplifies the digitalmotor control signals from the APC 31 to levels suitable for driving themotor 36.

Paper Pull Sensor

A paper pull sensor 50 detects a user's attempt to pull a photo from thecamera unit during the printing process. The APC 31 reads this sensor50, and activates the guillotine 41 if the condition occurs. The paperpull sensor 50 is incorporated to make the camera more ‘foolproof’ inoperation. Were the user to pull the paper out forcefully duringprinting, the print mechanism 44 or print roll 42 may (in extreme cases)be damaged. Since it is acceptable to pull out the ‘pod’ from a Polaroidtype camera before it is fully ejected, the public has been ‘trained’ todo this. Therefore, they are unlikely to heed printed instructions notto pull the paper.

The Artcam preferably restarts the photo print process after theguillotine 41 has cut the paper after pull sensing.

The pull sensor can be implemented as a strain gauge sensor, or as anoptical sensor detecting a small plastic flag, which is deflected by thetorque that occurs on the paper drive rollers when the paper is pulled.The latter implementation is recommendation for low cost.

Paper Guillotine Actuator 40

The paper guillotine actuator 40 is a small actuator which causes theguillotine 41 to cut the paper either at the end of a photograph, orwhen the paper pull sensor 50 is activated.

The guillotine actuator 40 is a small circuit, which amplifies aguillotine control signal from the APC tot the level required by theactuator 41.

Artcard 9

The Artcard 9 is a program storage medium for the Artcam unit. As notedpreviously, the programs are in the form of Vark scripts. Vark is apowerful image processing language especially developed for the Artcamunit. Each Artcard 9 contains one Vark script, and thereby defines oneimage processing style.

Preferably, the VARK language is highly image processing specific. Bybeing highly image processing specific, the amount of storage requiredto store the details on the card are substantially reduced. Further, theease with which new programs can be created, including enhanced effects,is also substantially increased. Preferably, the language includesfacilities for handling many image processing functions including imagewarping via a warp map, convolution, color lookup tables, posterizing animage, adding noise to an image, image enhancement filters, paintingalgorithms, brush jittering and manipulation edge detection filters,tiling, illumination via light sources, bump maps, text, face detectionand object detection attributes, fonts, including three dimensionalfonts, and arbitrary complexity pre-rendered icons. Further details ofthe operation of the Vark language interpreter are containedhereinafter.

Hence, by utilizing the language constructs as defined by the createdlanguage, new affects on arbitrary images can be created and constructedfor inexpensive storage on Artcard and subsequent distribution to cameraowners. Further, on one surface of the card can be provided an exampleillustrating the effect that a particular VARK script, stored on theother surface of the card, will have on an arbitrary captured image.

By utilizing such a system, camera technology can be distributed withouta great fear of obsolescence in that, provided a VARK interpreter isincorporated in the camera device, a device independent scenario isprovided whereby the underlying technology can be completely varied overtime. Further, the VARK scripts can be updated as new filters arecreated and distributed in an inexpensive manner, such as via simplecards for card reading.

The Artcard 9 is a piece of thin white plastic with the same format as acredit card (86 mm long by 54 mm wide). The Artcard is printed on bothsides using a high resolution ink jet printer. The inkjet printertechnology is assumed to be the same as that used in the Artcam, with1600 dpi (63 dpmm) resolution. A major feature of the Artcard 9 is lowmanufacturing cost. Artcards can be manufactured at high speeds as awide web of plastic film. The plastic web is coated on both sides with ahydrophilic dye fixing layer. The web is printed simultaneously on bothsides using a ‘pagewidth’ color ink jet printer. The web is then cut andpunched into individual cards. On one face of the card is printed ahuman readable representation of the effect the Artcard 9 will have onthe sensed image. This can be simply a standard image, which has beenprocessed using the Vark script stored on the back face of the card.

On the back face of the card is printed an array of dots which can bedecoded into the Vark script that defines the image processing sequence.The print area is 80 mm×50 mm, giving a total of 15,876,000 dots. Thisarray of dots could represent at least 1.89 Mbytes of data. To achievehigh reliability, extensive error detection and correction isincorporated in the array of dots. This allows a substantial portion ofthe card to be defaced, worn, creased, or dirty with no effect on dataintegrity. The data coding used is Reed-Solomon coding, with half of thedata devoted to error correction. This allows the storage of 967 Kbytesof error corrected data on each Artcard 9.

Linear Image Sensor 34

The Artcard linear sensor 34 converts the aforementioned Artcard dataimage to electrical signals. As with the area image sensor 2, 4, thelinear image sensor can be fabricated using either CCD or APS CMOStechnology. The active length of the image sensor 34 is 50 mm, equal tothe width of the data array on the Artcard 9. To satisfy Nyquist'ssampling theorem, the resolution of the linear image sensor 34 must beat least twice the highest spatial frequency of the Artcard opticalimage reaching the image sensor. In practice, data detection is easierif the image sensor resolution is substantially above this. A resolutionof 4800 dpi (189 dpmm) is chosen, giving a total of 9,450 pixels. Thisresolution requires a pixel sensor pitch of 5.3 μm. This can readily beachieved by using four staggered rows of 20 μm pixel sensors.

The linear image sensor is mounted in a special package, which includesa LED 65 to illuminate the Artcard 9 via a light-pipe (not shown).

The Artcard reader light-pipe can be a molded light-pipe which hasseveral function:

1. It diffuses the light from the LED over the width of the card usingtotal internal reflection facets.

2. It focuses the light onto a 16 μm wide strip of the Artcard 9 usingan integrated cylindrical lens.

3. It focuses light reflected from the Artcard onto the linear imagesensor pixels using a molded array of micro lenses.

The operation of the Artcard reader is explained further hereinafter.

Artcard Reader Motor 37

The Artcard reader motor propels the Artcard past the linear imagesensor 34 at a relatively constant rate. As it may not be cost effectiveto include extreme precision mechanical components in the Artcardreader, the motor 37 is a standard miniature motor geared down to anappropriate speed to drive a pair of rollers, which move the Artcard 9.The speed variations, rumble, and other vibrations will affect the rawimage data as circuitry within the APC 31 includes extensivecompensation for these effects to reliably read the Artcard data.

The motor 37 is driven in reverse when the Artcard is to be ejected.

Artcard Motor Driver 61

The Artcard motor driver 61 is a small circuit, which amplifies thedigital motor control signals from the APC 31 to levels suitable fordriving the motor 37.

Card Insertion Sensor 49

The card insertion sensor 49 is an optical sensor, which detects thepresence of a card as it is being inserted in the card reader 34. Upon asignal from this sensor 49, the APC 31 initiates the card readingprocess, including the activation of the Artcard reader motor 37.

Card Eject Button 16

A card eject button 16 (FIG. 1) is used by the user to eject the currentArtcard, so that another Artcard can be inserted. The APC 31 detects thepressing of the button, and reverses the Artcard reader motor 37 toeject the card.

Card Status Indicator 66

A card status indicator 66 is provided to signal the user as to thestatus of the Artcard reading process. This can be a standard bi-color(red/green) LED. When the card is successfully read, and data integrityhas been verified, the LED lights up green continually. If the card isfaulty, then the LED lights up red.

If the camera is powered from a 1.5 V instead of 3V battery, then thepower supply voltage is less than the forward voltage drop of the greedLED, and the LED will not light. In this case, red LEDs can be used, orthe LED can be powered from a voltage pump, which also powers othercircuits in the Artcam which require higher voltage.

64 Mbit DRAM 33

To perform the wide variety of image processing effects, the camerautilizes 8 Mbytes of memory 33. This can be provided by a single 64 Mbitmemory chip. Of course, with changing memory technology increased Dramstorage sizes may be substituted.

High speed access to the memory chip is required. This can be achievedby using a Rambus DRAM (burst access rate of 500 Mbytes per second) orchips using the new open standards such as double data rate (DDR) SDRAMor Synclink DRAM.

Camera Authentication Chip

The camera authentication chip 54 is identical to the print rollauthentication chip 53, except that it has different information storedin it. The camera authentication chip 54 has three main purposes:

1. To provide a secure means of comparing authentication codes with theprint roll authentication chip;

2. To provide storage for manufacturing information, such as the serialnumber of the camera;

3. To provide a small amount of non-volatile memory for storage of userinformation.

Displays

The Artcam includes an optional color display 5 and small status display15. Lowest cost consumer cameras may include a color image display, suchas a small TFT LCD 5 similar to those found on some digital cameras andcamcorders. The color display 5 is a major cost element of theseversions of Artcam, and the display 5 plus back light are a major powerconsumption drain.

Status Display 15

The status display 15 is a small passive segment based LCD, similar tothose currently provided on silver halide and digital cameras. Its mainfunction is to show the number of prints remaining in the print roll 42and icons for various standard camera features, such as flash andbattery status.

Color Display 5

The color display 5 is a full motion image display which operates as aviewfinder, as a verification of the image to be printed, and as a userinterface display. The cost of the display 5 is approximatelyproportional to its area, so large displays (say 4″ diagonal) unit willbe restricted to expensive versions of the Artcam unit. Smallerdisplays, such as color camcorder viewfinder TFT's at around 1″, may beeffective for mid-range Artcams.

Zoom Lens (Not Shown)

The Artcam can include a zoom lens. This can be a standardelectronically controlled zoom lens, identical to one which would beused on a standard electronic camera, and similar to pocket camera zoomlenses. A referred version of the Artcam unit may include standardinterchangeable 35 mm SLR lenses.

Autofocus Motor 39

The autofocus motor 39 changes the focus of the zoom lens. The motor isa miniature motor geared down to an appropriate speed to drive theautofocus mechanism.

Autofocus Motor Driver 63

The autofocus motor driver 63 is a small circuit which amplifies thedigital motor control signals from the APC 31 to levels suitable fordriving the motor 39.

Zoom Motor 38

The zoom motor 38 moves the zoom front lenses in and out. The motor is aminiature motor geared down to an appropriate speed to drive the zoommechanism.

Zoom Motor Driver 62

The zoom motor driver 62 is a small circuit which amplifies the digitalmotor control signals from the APC 31 to levels suitable for driving themotor.

Communications

The ACP 31 contains a universal serial bus (USB) interface 52 forcommunication with personal computers. Not all Artcam models areintended to include the USB connector. However, the silicon arearequired for a USB circuit 52 is small, so the interface can be includedin the standard ACP.

Optional Keyboard 57

The Artcam unit may include an optional miniature keyboard 57 forcustomizing text specified by the Artcard. Any text appearing in anArtcard image may be editable, even if it is in a complex metallic 3Dfont. The miniature keyboard includes a single line alphanumeric LCD todisplay the original text and edited text. The keyboard may be astandard accessory.

The ACP 31 contains a serial communications circuit for transferringdata to and from the miniature keyboard.

Power Supply

The Artcam unit uses a battery 48. Depending upon the Artcam options,this is a 3V Lithium cell, 1.5 V AA alkaline cells, or other batteryarrangement.

Power Management Unit 51

Power consumption is an important design constraint in the Artcam. It isdesirable that either standard camera batteries (such as 3V lithiumbatters) or standard AA or AAA alkaline cells can be used. While theelectronic complexity of the Artcam unit is dramatically higher than 35mm photographic cameras, the power consumption need not becommensurately higher. Power in the Artcam can be carefully managed withall units being turned off when not in use.

The most significant current drains are the ACP 31, the area imagesensors 2,4, the printer 44 various motors, the flash unit 56, and theoptional color display 5 dealing with each part separately:

1. ACP: If fabricated using 0.25 μm CMOS, and running on 1.5V, the ACPpower consumption can be quite low. Clocks to various parts of the ACPchip can be quite low. Clocks to various parts of the ACP chip can beturned off when not in use, virtually eliminating standby currentconsumption. The ACP will only fully used for approximately 4 secondsfor each photograph printed.

2. Area image sensor: power is only supplied to the area image sensorwhen the user has their finger on the button.

3. The printer power is only supplied to the printer when actuallyprinting. This is for around 2 seconds for each photograph. Even so,suitably lower power consumption printing should be used.

4. The motors required in the Artcam are all low power miniature motors,and are typically only activated for a few seconds per photo.

5. The flash unit 45 is only used for some photographs. Its powerconsumption can readily be provided by a 3V lithium battery for areasonably battery life.

6. The optional color display 5 is a major current drain for tworeasons: it must be on for the whole time that the camera is in use, anda backlight will be required if a liquid crystal display is used.Cameras that incorporate a color display will require a larger batteryto achieve acceptable batter life.

Flash Unit 56

The flash unit 56 can be a standard miniature electronic flash forconsumer cameras.

Overview of the ACP 31

FIG. 3 illustrates the Artcam Central Processor (ACP) 31 in more detail.The Artcam Central Processor provides all of the processing power forArtcam. It is designed for a 0.25 micron CMOS process, withapproximately 1.5 million transistors and an area of around 50 mm². TheACP 31 is a complex design, but design effort can be reduced by the useof datapath compilation techniques, macrocells, and IP cores. The ACP 31contains:

-   -   A RISC CPU core 72    -   A 4 way parallel VLIW Vector Processor 74    -   A Direct RAMbus interface 81    -   A CMOS image sensor interface 83    -   A CMOS linear image sensor interface 88    -   A USB serial interface 52    -   An infrared keyboard interface 55    -   A numeric LCD interface 84, and    -   A color TFT LCD interface 88    -   A 4 Mbyte Flash memory 70 for program storage 70

The RISC CPU, Direct RAMbus interface 81, CMOS sensor interface 83 andUSB serial interface 52 can be vendor supplied cores. The ACP 31 isintended to run at a clock speed of 200 MHz on 3V externally and 1.5Vinternally to minimize power consumption. The CPU core needs only to runat 100 MHz. The following two block diagrams give two views of the ACP31:

-   -   A view of the ACP 31 in isolation

An example Artcam showing a high-level view of the ACP 31 connected tothe rest of the Artcam hardware.

Image Access

As stated previously, the DRAM Interface 81 is responsible forinterfacing between other client portions of the ACP chip and the RAMBUSDRAM. In effect, each module within the DRAM Interface is an addressgenerator.

There are three logical types of images manipulated by the ACP. Theyare:

-   -   CCD Image, which is the Input Image captured from the CCD.    -   Internal Image format—the Image format utilised internally by        the Artcam device.    -   Print Image—the Output Image format printed by the Artcam

These images are typically different in color space, resolution, and theoutput & input color spaces, which can vary from camera to camera. Forexample, a CCD image on a low-end camera may be a different resolution,or have different color characteristics from that used in a high-endcamera. However all internal image formats are the same format in termsof color space across all cameras.

In addition, the three image types can vary with respect to whichdirection is ‘up’. The physical orientation of the camera causes thenotion of a portrait or landscape image, and this must be maintainedthroughout processing. For this reason, the internal image is alwaysoriented correctly, and rotation is performed on images obtained fromthe CCD and during the print operation.

CPU Core (CPU) 72

The ACP 31 incorporates a 32 bit RISC CPU 72 to run the Vark imageprocessing language interpreter and to perform Artcam's generaloperating system duties. A wide variety of CPU cores are suitable: itcan be any processor core with sufficient processing power to performthe required core calculations and control functions fast enough to metconsumer expectations. Examples of suitable cores are: MIPS R4000 corefrom LSI Logic, StrongARM core. There is no need to maintain instructionset continuity between different Artcam models. Artcard compatibility ismaintained irrespective of future processor advances and changes,because the Vark interpreter is simply re-compiled for each newinstruction set. The ACP 31 architecture is therefore also free toevolve. Different ACP 31 chip designs may be fabricated by differentmanufacturers, without requiring to license or port the CPU core. Thisdevice independence avoids the chip vendor lock-in such as has occurredin the PC market with Intel. The CPU operates at 100 MHz, with a singlecycle time of 10 ns. It must be fast enough to run the Vark interpreter,although the VLIW Vector Processor 74 is responsible for most of thetime-critical operations.

Program Cache 72

Although the program code is stored in on-chip Flash memory 70, it isunlikely that well packed Flash memory 70 will be able to operate at the10 ns cycle time required by the CPU. Consequently a small cache isrequired for good performance. 16 cache lines of 32 bytes each aresufficient, for a total of 512 bytes. The program cache 72 is defined inthe chapter entitled Program cache 72.

Data Cache 76

A small data cache 76 is required for good performance. This requirementis mostly due to the use of a RAMbus DRAM, which can provide high-speeddata in bursts, but is inefficient for single byte accesses. The CPU hasaccess to a memory caching system that allows flexible manipulation ofCPU data cache 76 sizes. A minimum of 16 cache lines (512 bytes) isrecommended for good performance.

CPU Memory Model

An Artcam's CPU memory model consists of a 32 MB area. It consists of 8MB of physical RDRAM off-chip in the base model of Artcam, withprovision for up to 16 MB of off-chip memory. There is a 4 MB Flashmemory 70 on the ACP 31 for program storage, and finally a 4 MB addressspace mapped to the various registers and controls of the ACP 31. Thememory map then, for an Artcam is as follows:

Contents Size Base Artcam DRAM 8 MB Extended DRAM 8 MB Program memory(on ACP 31 in Flash memory 70) 4 MB Reserved for extension of programmemory 4 MB ACP 31 registers and memory-mapped I/O 4 MB Reserved 4 MBTOTAL 32 MB 

A straightforward way of decoding addresses is to use address bits23-24:

-   -   If bit 24 is clear, the address is in the lower 16-MB range, and        hence can be satisfied from DRAM and the Data cache 76. In most        cases the DRAM will only be 8 MB, but 16 MB is allocated to        cater for a higher memory model Artcams.    -   If bit 24 is set, and bit 23 is clear, then the address        represents the Flash memory 70 4 Mbyte range and is satisfied by        the Program cache 72.    -   If bit 24=1 and bit 23=1, the address is translated into an        access over the low speed bus to the requested component in the        AC by the CPU Memory Decoder 68.

Flash Memory 70

The ACP 31 contains a 4 Mbyte Flash memory 70 for storing the Artcamprogram. It is envisaged that Flash memory 70 will have denser packingcoefficients than masked ROM, and allows for greater flexibility fortesting camera program code. The downside of the Flash memory 70 is theaccess time, which is unlikely to be fast enough for the 100 MHzoperating speed (10 ns cycle time) of the CPU. A fast ProgramInstruction cache 77 therefore acts as the interface between the CPU andthe slower Flash memory 70.

Program Cache 72

A small cache is required for good CPU performance. This requirement isdue to the slow speed Flash memory 70 which stores the Program code. 16cache lines of 32 bytes each are sufficient, for a total of 512 bytes.The Program cache 72 is a read only cache. The data used by CPU programscomes through the CPU Memory Decoder 68 and if the address is in DRAM,through the general Data cache 76. The separation allows the CPU tooperate independently of the VLIW Vector Processor 74. If the datarequirements are low for a given process, it can consequently operatecompletely out of cache.

Finally, the Program cache 72 can be read as data by the CPU rather thanpurely as program instructions. This allows tables, microcode for theVLIW etc to be loaded from the Flash memory 70. Addresses with bit 24set and bit 23 clear are satisfied from the Program cache 72.

CPU Memory Decoder 68

The CPU Memory Decoder 68 is a simple decoder for satisfying CPU dataaccesses. The Decoder translates data addresses into internal ACPregister accesses over the internal low speed bus, and therefore allowsfor memory mapped I/O of ACP registers. The CPU Memory Decoder 68 onlyinterprets addresses that have bit 24 set and bit 23 clear. There is nocaching in the CPU Memory Decoder 68.

DRAM Interface 81

The DRAM used by the Artcam is a single channel 64 Mbit (8 MB) RAMbusRDRAM operating at 1.6 GB/sec. RDRAM accesses are by a single channel(16-bit data path) controller. The RDRAM also has several usefuloperating modes for low power operation. Although the Rambusspecification describes a system with random 32 byte transfers ascapable of achieving a greater than 95% efficiency, this is not true ifonly part of the 32 bytes are used. Two reads followed by two writes tothe same device yields over 86% efficiency. The primary latency isrequired for bus turn-around going from a Write to a Read, and sincethere is a Delayed Write mechanism, efficiency can be further improved.With regards to writes, Write Masks allow specific subsets of bytes tobe written to. These write masks would be set via internal cache “dirtybits”. The upshot of the Rambus Direct RDRAM is a throughput of >1GB/sec is easily achievable, and with multiple reads for every write(most processes) combined with intelligent algorithms making good use of32 byte transfer knowledge, transfer rates of >1.3 GB/sec are expected.Every 10 ns, 16 bytes can be transferred to or from the core.

DRAM Organization

The DRAM organization for a base model (8 MB RDRAM) Artcam is asfollows:

Contents Size Program scratch RAM 0.50 MB Artcard data 1.00 MB PhotoImage, captured from CMOS Sensor 0.50 MB Print Image (compressed) 2.25MB 1 Channel of expanded Photo Image 1.50 MB 1 Image Pyramid of singlechannel 1.00 MB Intermediate Image Processing 1.25 MB TOTAL   8 MB

Notes:

-   Uncompressed, the Print Image requires 4.5 MB (1.5 MB per channel).    To accommodate other objects in the 8 MB model, the Print Image    needs to be compressed. If the chrominance channels are compressed    by 4:1 they require only 0.375 MB each).-   The memory model described here assumes a single 8 MB RDRAM. Other    models of the Artcam may have more memory, and thus not require    compression of the Print Image. In addition, with more memory a    larger part of the final image can be worked on at once, potentially    giving a speed improvement.-   Note that ejecting or inserting an Artcard invalidates the 5.5 MB    area holding the Print Image, 1 channel of expanded photo image, and    the image pyramid. This space may be safely used by the Artcard    Interface for decoding the Artcard data.

Data Cache 76

The ACP 31 contains a dedicated CPU instruction cache 77 and a generaldata cache 76. The Data cache 76 handles all DRAM requests (reads andwrites of data) from the CPU, the VLIW Vector Processor 74, and theDisplay Controller 88. These requests may have very different profilesin terms of memory usage and algorithmic timing requirements. Forexample, a VLIW process may be processing an image in linear memory, andlookup a value in a table for each value in the image. There is littleneed to cache much of the image, but it may be desirable to cache theentire lookup table so that no real memory access is required. Becauseof these differing requirements, the Data cache 76 allows for anintelligent definition of caching.

Although the Rambus DRAM interface 81 is capable of very high-speedmemory access (an average throughput of 32 bytes in 25 ns), it is notefficient dealing with single byte requests. In order to reduceeffective memory latency, the ACP 31 contains 128 cache lines. Eachcache line is 32 bytes wide. Thus the total amount of data cache 76 is4096 bytes (4 KB). The 128 cache lines are configured into 16programmable-sized groups. Each of the 16 groups must be a contiguousset of cache lines. The CPU is responsible for determining how manycache lines to allocate to each group. Within each group cache lines arefilled according to a simple Least Recently Used algorithm. In terms ofCPU data requests, the Data cache 76 handles memory access requests thathave address bit 24 clear. If bit 24 is clear, the address is in thelower 16 MB range, and hence can be satisfied from DRAM and the Datacache 76. In most cases the DRAM will only be 8 MB, but 16 MB isallocated to cater for a higher memory model Artcam. If bit 24 is set,the address is ignored by the Data cache 76.

All CPU data requests are satisfied from Cache Group 0. A minimum of 16cache lines is recommended for good CPU performance, although the CPUcan assign any number of cache lines (except none) to Cache Group 0. Theremaining Cache Groups (1 to 15) are allocated according to the currentrequirements. This could mean allocation to a VLIW Vector Processor 74program or the Display Controller 88. For example, a 256 byte lookuptable required to be permanently available would require 8 cache lines.Writing out a sequential image would only require 2-4 cache lines(depending on the size of record being generated and whether writerequests are being Write Delayed for a significant number of cycles).Associated with each cache line byte is a dirty bit, used for creating aWrite Mask when writing memory to DRAM. Associated with each cache lineis another dirty bit, which indicates whether any of the cache linebytes has been written to (and therefore the cache line must be writtenback to DRAM before it can be reused). Note that it is possible for twodifferent Cache Groups to be accessing the same address in memory and toget out of sync. The VLIW program writer is responsible to ensure thatthis is not an issue. It could be perfectly reasonable, for example, tohave a Cache Group responsible for reading an image, and another CacheGroup responsible for writing the changed image back to memory again. Ifthe images are read or written sequentially there may be advantages inallocating cache lines in this manner. A total of 8 buses 182 connectthe VLIW Vector Processor 74 to the Data cache 76. Each bus is connectedto an I/O Address Generator. (There are 2 I/O Address Generators 189,190 per Processing Unit 178, and there are 4 Processing Units in theVLIW Vector Processor 74. The total number of buses is therefore 8.)

In any given cycle, in addition to a single 32 bit (4 byte) access tothe CPU's cache group (Group 0), 4 simultaneous accesses of 16 bits (2bytes) to remaining cache groups are permitted on the 8 VLIW VectorProcessor 74 buses. The Data cache 76 is responsible for fairlyprocessing the requests. On a given cycle, no more than 1 request to aspecific Cache Group will be processed. Given that there are 8 AddressGenerators 189, 190 in the VLIW Vector Processor 74, each one of thesehas the potential to refer to an individual Cache Group. However it ispossible and occasionally reasonable for 2 or more Address Generators189, 190 to access the same Cache Group. The CPU is responsible forensuring that the Cache Groups have been allocated the correct number ofcache lines, and that the various Address Generators 189, 190 in theVLIW Vector Processor 74 reference the specific Cache Groups correctly.

The Data cache 76 as described allows for the Display Controller 88 andVLIW Vector Processor 74 to be active simultaneously. If the operationof these two components were deemed to never occur simultaneously, atotal 9 Cache Groups would suffice. The CPU would use Cache Group 0, andthe VLIW Vector Processor 74 and the Display Controller 88 would sharethe remaining 8 Cache Groups, requiring only 3 bits (rather than 4) todefine which Cache Group would satisfy a particular request.

JTAG Interface 85

A standard JTAG (Joint Test Action Group) Interface is included in theACP 31 for testing purposes. Due to the complexity of the chip, avariety of testing techniques are required, including BIST (Built InSelf Test) and functional block isolation. An overhead of 10% in chiparea is assumed for overall chip testing circuitry. The test circuitryis beyond the scope of this document.

Serial Interfaces USB Serial Port Interface 52

This is a standard USB serial port, which is connected to the internalchip low speed bus, thereby allowing the CPU to control it.

Keyboard Interface 65

This is a standard low-speed serial port, which is connected to theinternal chip low speed bus, thereby allowing the CPU to control it. Itis designed to be optionally connected to a keyboard to allow simpledata input to customize prints.

Authentication Chip Serial Interfaces 64

These are 2 standard low-speed serial ports, which are connected to theinternal chip low speed bus, thereby allowing the CPU to control them.The reason for having 2 ports is to connect to both the on-cameraAuthentication chip, and to the print-roll Authentication chip usingseparate lines. Only using 1 line may make it possible for a cloneprint-roll manufacturer to design a chip which, instead of generating anauthentication code, tricks the camera into using the code generated bythe authentication chip in the camera.

Parallel Interface 67

The parallel interface connects the ACP 31 to individual staticelectrical signals. The CPU is able to control each of these connectionsas memory-mapped I/O via the low speed bus The following table is a listof connections to the parallel interface:

Connection Direction Pins Paper transport stepper motor Out 4 Artcardstepper motor Out 4 Zoom stepper motor Out 4 Guillotine motor Out 1Flash trigger Out 1 Status LCD segment drivers Out 7 Status LCD commondrivers Out 4 Artcard illumination LED Out 1 Artcard status LED(red/green) In 2 Artcard sensor In 1 Paper pull sensor In 1 Orientationsensor In 2 Buttons In 4 TOTAL 36

VLIW Input and Output FIFOs 78, 79

The VLIW Input and Output FIFOs are 8 bit wide FIFOs used forcommunicating between processes and the VLIW Vector Processor 74. BothFIFOs are under the control of the VLIW Vector Processor 74, but can becleared and queried (e.g. for status) etc by the CPU.

VLIW Input FIFO 78

A client writes 8-bit data to the VLIW Input FIFO 78 in order to havethe data processed by the VLIW Vector Processor 74. Clients include theImage Sensor Interface, Artcard Interface, and CPU. Each of theseprocesses is able to offload processing by simply writing the data tothe FIFO, and letting the VLIW Vector Processor 74 do all the hard work.An example of the use of a client's use of the VLIW Input FIFO 78 is theImage Sensor Interface (ISI 83). The ISI 83 takes data from the ImageSensor and writes it to the FIFO. A VLIW process takes it from the FIFO,transforming it into the correct image data format, and writing it outto DRAM. The ISI 83 becomes much simpler as a result.

VLIW Output FIFO 79

The VLIW Vector Processor 74 writes 8-bit data to the VLIW Output FIFO79 where clients can read it. Clients include the Print Head Interfaceand the CPU. Both of these clients is able to offload processing bysimply reading the already processed data from the FIFO, and letting theVLIW Vector Processor 74 do all the hard work. The CPU can also beinterrupted whenever data is placed into the VLIW Output FIFO 79,allowing it to only process the data as it becomes available rather thanpolling the FIFO continuously. An example of the use of a client's useof the VLIW Output FIFO 79 is the Print Head Interface (PHI 62). A VLIWprocess takes an image, rotates it to the correct orientation, colorconverts it, and dithers the resulting image according to the print headrequirements. The PHI 62 reads the dithered formatted 8-bit data fromthe VLIW Output FIFO 79 and simply passes it on to the Print Headexternal to the ACP 31. The PHI 62 becomes much simpler as a result.

VLIW Vector Processor 74

To achieve the high processing requirements of Artcam, the ACP 31contains a VLIW (Very Long Instruction Word) Vector Processor. The VLIWprocessor is a set of 4 identical Processing Units (PU e.g. 178) workingin parallel, connected by a crossbar switch 183. Each PU e.g. 178 canperform four 8-bit multiplications, eight 8-bit additions, three 32-bitadditions, I/O processing, and various logical operations in each cycle.The PUs e.g. 178 are microcoded, and each has two Address Generators189, 190 to allow full use of available cycles for data processing. Thefour PUs e.g. 178 are normally synchronized to provide a tightlyinteracting VLIW processor. Clocking at 200 MHz, the VLIW VectorProcessor 74 runs at 12 Gops (12 billion operations per second).Instructions are tuned for image processing functions such as warping,artistic brushing, complex synthetic illumination, color transforms,image filtering, and compositing. These are accelerated by two orders ofmagnitude over desktop computers.

As shown in more detail in FIG. 3( a), the VLIW Vector Processor 74 is 4PUs e.g. 178 connected by a crossbar switch 183 such that each PU e.g.178 provides two inputs to, and takes two outputs from, the crossbarswitch 183. Two common registers form a control and synchronizationmechanism for the PUs e.g. 178. 8 Cache buses 182 allow connectivity toDRAM via the Data cache 76, with 2 buses going to each PU e.g. 178 (1bus per I/O Address Generator).

Each PU e.g. 178 consists of an ALU 188 (containing a number ofregisters & some arithmetic logic for processing data), some microcodeRAM 196, and connections to the outside world (including other ALUs). Alocal PU state machine runs in microcode and is the means by which thePU e.g. 178 is controlled. Each PU e.g. 178 contains two I/O AddressGenerators 189, 190 controlling data flow between DRAM (via the Datacache 76) and the ALU 188 (via Input FIFO and Output FIFO). The addressgenerator is able to read and write data (specifically images in avariety of formats) as well as tables and simulated FIFOs in DRAM. Theformats are customizable under software control, but are not microcoded.Data taken from the Data cache 76 is transferred to the ALU 188 via the16-bit wide Input FIFO. Output data is written to the 16-bit wide OutputFIFO and from there to the Data cache 76. Finally, all PUs e.g. 178share a single 8-bit wide VLIW Input FIFO 78 and a single 8-bit wideVLIW Output FIFO 79. The low speed data bus connection allows the CPU toread and write registers in the PU e.g. 178, update microcode, as wellas the common registers shared by all PUs e.g. 178 in the VLIW VectorProcessor 74. Turning now to FIG. 4, a closer detail of the internals ofa single PU e.g. 178 can be seen, with components and control signalsdetailed in subsequent hereinafter:

Microcode

Each PU e.g. 178 contains a microcode RAM 196 to hold the program forthat particular PU e.g. 178. Rather than have the microcode in ROM, themicrocode is in RAM, with the CPU responsible for loading it up. For thesame space on chip, this tradeoff reduces the maximum size of any onefunction to the size of the RAM, but allows an unlimited number offunctions to be written in microcode. Functions implemented usingmicrocode include Vark acceleration, Artcard reading, and Printing. TheVLIW Vector Processor 74 scheme has several advantages for the case ofthe ACP 31:

-   -   Hardware design complexity is reduced    -   Hardware risk is reduced due to reduction in complexity    -   Hardware design time does not depend on all Vark functionality        being implemented in dedicated silicon    -   Space on chip is reduced overall (due to large number of        processes able to be implemented as microcode)    -   Functionality can be added to Vark (via microcode) with no        impact on hardware design time

Size and Content

The CPU loaded microcode RAM 196 for controlling each PU e.g. 178 is 128words, with each word being 96 bits wide. A summary of the microcodesize for control of various units of the PU e.g. 178 is listed in thefollowing table:

Process Block Size (bits) Status Output 3 Branching (microcode control)11 In 8 Out 6 Registers 7 Read 10 Write 6 Barrel Shifter 12Adder/Logical 14 Multiply/Interpolate 19 TOTAL 96

With 128 instruction words, the total microcode RAM 196 per PU e.g. 178is 12,288 bits, or 1.5 KB exactly. Since the VLIW Vector Processor 74consists of 4 identical PUs e.g. 178 this equates to 6,144 bytes,exactly 6 KB. Some of the bits in a microcode word are directly used ascontrol bits, while others are decoded. See the various unitdescriptions that detail the interpretation of each of the bits of themicrocode word.

Synchronization Between PUs e.g. 178

Each PU e.g. 178 contains a 4 bit Synchronization Register 197. It is amask used to determine which PUs e.g. 178 work together, and has one bitset for each of the corresponding PUs e.g. 178 that are functioning as asingle process. For example, if all of the PUs e.g. 178 were functioningas a single process, each of the 4 Synchronization Register 197 s wouldhave all 4 bits set. If there were two asynchronous processes of 2 PUse.g. 178 each, two of the PUs e.g. 178 would have 2 bits set in theirSynchronization Register 197 s (corresponding to themselves), and theother two would have the other 2 bits set in their SynchronizationRegister 197 s (corresponding to themselves).

The Synchronization Register 197 is used in two basic ways:

-   -   Stopping and starting a given process in synchrony    -   Suspending execution within a process

Stopping and Starting Processes

The CPU is responsible for loading the microcode RAM 196 and loading theexecution address for the first instruction (usually 0). When the CPUstarts executing microcode, it begins at the specified address.

Execution of microcode only occurs when all the bits of theSynchronization Register 197 are also set in the Common SynchronizationRegister 197. The CPU therefore sets up all the PUs e.g. 178 and thenstarts or stops processes with a single write to the CommonSynchronization Register 197.

This synchronization scheme allows multiple processes to be runningasynchronously on the PUs e.g. 178, being stopped and started asprocesses rather than one PU e.g. 178 at a time.

Suspending Execution within a Process

In a given cycle, a PU e.g. 178 may need to read from or write to a FIFO(based on the opcode of the current microcode instruction). If the FIFOis empty on a read request, or full on a write request, the FIFO requestcannot be completed. The PU e.g. 178 will therefore assert itsSuspendProcess control signal 198. The SuspendProcess signals from allPUs e.g. 178 are fed back to all the PUs e.g. 178. The SynchronizationRegister 197 is ANDed with the 4 SuspendProcess bits, and if the resultis non-zero, none of the PU e.g. 178's register WriteEnables or FIFOstrobes will be set. Consequently none of the PUs e.g. 178 that form thesame process group as the PU e.g. 178 that was unable to complete itstask will have their registers or FIFOs updated during that cycle. Thissimple technique keeps a given process group in synchronization. Eachsubsequent cycle the PU e.g. 178's state machine will attempt tore-execute the microcode instruction at the same address, and willcontinue to do so until successful. Of course the Common SynchronizationRegister 197 can be written to by the CPU to stop the entire process ifnecessary. This synchronization scheme allows any combinations of PUse.g. 178 to work together, each group only affecting its co-workers withregards to suspension due to data not being ready for reading orwriting.

Control and Branching

During each cycle, each of the four basic input and calculation unitswithin a PU e.g. 178's ALU 188 (Read, Adder/Logic, Multiply/Interpolate,and Barrel Shifter) produces two status bits: a Zero flag and a Negativeflag indicating whether the result of the operation during that cyclewas 0 or negative. Each cycle one of those 4 status bits is chosen bymicrocode instructions to be output from the PU e.g. 178. The 4 statusbits (1 per PU e.g. 178's ALU 188) are combined into a 4 bit CommonStatus Register 200. During the next cycle, each PU e.g. 178's microcodeprogram can select one of the bits from the Common Status Register 200,and branch to another microcode address dependant on the value of thestatus bit.

Status Bit

Each PU e.g. 178's ALU 188 contains a number of input and calculationunits. Each unit produces 2 status bits—a negative flag and a zero flag.One of these status bits is output from the PU e.g. 178 when aparticular unit asserts the value on the 1-bit tri-state status bit bus.The single status bit is output from the PU e.g. 178, and then combinedwith the other PU e.g. 178 status bits to update the Common StatusRegister 200. The microcode for determining the output status bit takesthe following form:

# Bits Description 2 Select unit whose status bit is to be output 00 =Adder unit 01 = Multiply/Logic unit 10 = Barrel Shift unit 11 = Readerunit 1 0 = Zero flag 1 = Negative flag 3 TOTAL

Within the ALU 188, the 2-bit Select Processor Block value is decodedinto four 1-bit enable bits, with a different enable bit sent to eachprocessor unit block. The status select bit (choosing Zero or Negative)is passed into all units to determine which bit is to be output onto thestatus bit bus.

Branching within Microcode

Each PU e.g. 178 contains a 7 bit Program Counter (PC) that holds thecurrent microcode address being executed. Normal program execution islinear, moving from address N in one cycle to address N+1 in the nextcycle. Every cycle however, a microcode program has the ability tobranch to a different location, or to test a status bit from the CommonStatus Register 200 and branch. The microcode for determining the nextexecution address takes the following form:

# Bits Description 2 00 = NOP (PC = PC + 1) 01 = Branch always 10 =Branch if status bit clear 11 = Branch if status bit set 2 Select statusbit from status word 7 Address to branch to (absolute address, 00-7F) 11TOTAL

ALU 188

FIG. 5 illustrates the ALU 188 in more detail. Inside the ALU 188 are anumber of specialized processing blocks, controlled by a microcodeprogram. The specialized processing blocks include:

-   -   Read Block 202, for accepting data from the input FIFOs    -   Write Block 203, for sending data out via the output FIFOs    -   Adder/Logical block 204, for addition & subtraction, comparisons        and logical operations    -   Multiply/Interpolate block 205, for multiple types of        interpolations and multiply/accumulates    -   Barrel Shift block 206, for shifting data as required    -   In block 207, for accepting data from the external crossbar        switch 183    -   Out block 208, for sending data to the external crossbar switch        183    -   Registers block 215, for holding data in temporary storage

Four specialized 32 bit registers hold the results of the 4 mainprocessing blocks:

-   -   M register 209 holds the result of the Multiply/Interpolate        block    -   L register 209 holds the result of the Adder/Logic block    -   S register 209 holds the result of the Barrel Shifter block    -   R register 209 holds the result of the Read Block 202

In addition there are two internal crossbar switches 213 m 214 for datatransport. The various process blocks are further expanded in thefollowing sections, together with the microcode definitions that pertainto each block. Note that the microcode is decoded within a block toprovide the control signals to the various units within.

Data Transfers Between PUs e.g. 178

Each PU e.g. 178 is able to exchange data via the external crossbar. APU e.g. 178 takes two inputs and outputs two values to the externalcrossbar. In this way two operands for processing can be obtained in asingle cycle, but cannot be actually used in an operation until thefollowing cycle.

In 207

This block is illustrated in FIG. 6 and contains two registers, In₁ andIn₂ that accept data from the external crossbar. The registers can beloaded each cycle, or can remain unchanged. The selection bits forchoosing from among the 8 inputs are output to the external crossbarswitch 183. The microcode takes the following form:

# Bits Description 1 0 = NOP 1 = Load In₁ from crossbar 3 Select Input 1from external crossbar 1 0 = NOP 1 = Load In₂ from crossbar 3 SelectInput 2 from external crossbar 8 TOTAL

Out 208

Complementing In is Out 208. The Out block is illustrated in more detailin FIG. 7. Out contains two registers, Out₁ and Out₂, both of which areoutput to the external crossbar each cycle for use by other PUs e.g.178. The Write unit is also able to write one of Out₁ or Out₂ to one ofthe output FIFOs attached to the ALU 188. Finally, both registers areavailable as inputs to Crossbar1 213, which therefore makes the registervalues available as inputs to other units within the ALU 188. Each cycleeither of the two registers can be updated according to microcodeselection. The data loaded into the specified register can be one ofD₀-D₃ (selected from Crossbar1 213) one of M, L, S, and R (selected fromCrossbar2 214), one of 2 programmable constants, or the fixed values 0or 1. The microcode for Out takes the following form:

# Bits Description 1 0 = NOP 1 = Load Register 1 Select Register to load[Out₁ or Out₂] 4 Select input [In₁, In₂, Out₁, Out₂, D₀, D₁, D₂, D₃, M,L, S, R, K₁, K₂, 0, 1] 6 TOTAL

Local Registers and Data Transfers within ALU 188

As noted previously, the ALU 188 contains four specialized 32-bitregisters to hold the results of the 4 main processing blocks:

-   -   M register 209 holds the result of the Multiply/Interpolate        block    -   L register 209 holds the result of the Adder/Logic block    -   S register 209 holds the result of the Barrel Shifter block    -   R register 209 holds the result of the Read Block 202

The CPU has direct access to these registers, and other units can selectthem as inputs via Crossbar2 214. Sometimes it is necessary to delay anoperation for one or more cycles. The Registers block contains four32-bit registers D₀-D₃ to hold temporary variables during processing.Each cycle one of the registers can be updated, while all the registersare output for other units to use via Crossbar1 213 (which also includesIn₁, In₂, Out₁ and Out₂). The CPU has direct access to these registers.The data loaded into the specified register can be one of D₀-D₃(selected from Crossbar1 213) one of M, L, S, and R (selected fromCrossbar2 214), one of 2 programmable constants, or the fixed values 0or 1. The Registers block 215 is illustrated in more detail in FIG. 8.The microcode for Registers takes the following form:

# Bits Description 1 0 = NOP 1 = Load Register 2 Select Register to load[D₀-D₃] 4 Select input [In₁, In₂, Out₁, Out₂, D₀, D₁, D₂, D₃, M, L, S,R, K₁, K₂, 0, 1] 7 TOTAL

Crossbar1 213

Crossbar1 213 is illustrated in more detail in FIG. 9. Crossbar1 213 isused to select from inputs In₁, In₂, Out₁, Out₂, D₀-D₃. 7 outputs aregenerated from Crossbar1 213: 3 to the Multiply/Interpolate Unit, 2 tothe Adder Unit, 1 to the Registers unit and 1 to the Out unit. Thecontrol signals for Crossbar1 213 come from the various units that usethe Crossbar inputs. There is no specific microcode that is separate forCrossbar1 213.

Crossbar2 214

Crossbar2 214 is illustrated in more detail in FIG. 10. Crossbar2 214 isused to select from the general ALU 188 registers M, L, S and R. 6outputs are generated from Crossbar1 213: 2 to the Multiply/InterpolateUnit, 2 to the Adder Unit, 1 to the Registers unit and 1 to the Outunit. The control signals for Crossbar2 214 come from the various unitsthat use the Crossbar inputs. There is no specific microcode that isseparate for Crossbar2 214.

Data Transfers Between PUs e.g. 178 and DRAM or External Processes

Returning to FIG. 4, PUs e.g. 178 share data with each other directlyvia the external crossbar. They also transfer data to and from externalprocesses as well as DRAM. Each PU e.g. 178 has 2 I/O Address Generators189, 190 for transferring data to and from DRAM. A PU e.g. 178 can senddata to DRAM via an I/O Address Generator's Output FIFO e.g. 186, oraccept data from DRAM via an I/O Address Generator's Input FIFO 187.These FIFOs are local to the PU e.g. 178. There is also a mechanism fortransferring data to and from external processes in the form of a commonVLIW Input FIFO 78 and a common VLIW Output FIFO 79, shared between allALUs. The VLIW Input and Output FIFOs are only 8 bits wide, and are usedfor printing, Artcard reading, transferring data to the CPU etc. Thelocal Input and Output FIFOs are 16 bits wide.

Read

The Read process block 202 of FIG. 5 is responsible for updating the ALU188's R register 209, which represents the external input data to a VLIWmicrocoded process. Each cycle the Read Unit is able to read from eitherthe common VLIW Input FIFO 78 (8 bits) or one of two local Input FIFOs(16 bits). A 32-bit value is generated, and then all or part of thatdata is transferred to the R register 209. The process can be seen inFIG. 11. The microcode for Read is described in the following table.Note that the interpretations of some bit patterns are deliberatelychosen to aid decoding.

# Bits Description 2 00 = NOP 01 = Read from VLIW Input FIFO 78 10 =Read from Local FIFO 1 11 = Read from Local FIFO 2 1 How manysignificant bits 0 = 8 bits (pad with 0 or sign extend) 1 = 16 bits(only valid for Local FIFO reads) 1 0 = Treat data as unsigned (pad with0) 1 = Treat data as signed (sign extend when reading from FIFO)r 2 Howmuch to shift data left by: 00 = 0 bits (no change) 01 = 8 bits 10 = 16bits 11 = 24 bits 4 Which bytes of R to update (hi to lo order byte)Each of the 4 bits represents 1 byte WriteEnable on R 10 TOTAL

Write

The Write process block is able to write to either the common VLIWOutput FIFO 79 or one of the two local Output FIFOs each cycle. Notethat since only 1 FIFO is written to in a given cycle, only one 16-bitvalue is output to all FIFOs, with the low 8 bits going to the VLIWOutput FIFO 79. The microcode controls which of the FIFOs gates in thevalue. The process of data selection can be seen in more detail in FIG.12. The source values Out₁ and Out₂ come from the Out block. They aresimply two registers. The microcode for Write takes the following form:

# Bits Description 2 00 = NOP 01 = Write VLIW Output FIFO 79 10 = Writelocal Output FIFO 1 11 = Write local Output FIFO 2 1 Select Output Value[Out₁ or Out₂] 3 Select part of Output Value to write (32 bits = 4 bytesABCD) 000 = 0D 001 = 0D 010 = 0B 011 = 0A 100 = CD 101 = BC 110 = AB 111= 0 6 TOTAL

Computational Blocks

Each ALU 188 has two computational process blocks, namely an Adder/Logicprocess block 204, and a Multiply/Interpolate process block 205. Inaddition there is a Barrel Shifter block to provide help to thesecomputational blocks. Registers from the Registers block 215 can be usedfor temporary storage during pipelined operations.

Barrel Shifter

The Barrel Shifter process block 206 is shown in more detail in FIG. 13and takes its input from the output of Adder/Logic orMultiply/Interpolate process blocks or the previous cycle's results fromthose blocks (ALU registers L and M). The 32 bits selected are barrelshifted an arbitrary number of bits in either direction (with signextension as necessary), and output to the ALU 188's S register 209. Themicrocode for the Barrel Shift process block is described in thefollowing table. Note that the interpretations of some bit patterns aredeliberately chosen to aid decoding.

# Bits Description 3 000 = NOP 001 = Shift Left (unsigned) 010 =Reserved 011 = Shift Left (signed) 100 = Shift right (unsigned, norounding) 101 = Shift right (unsigned, with rounding) 110 = Shift right(signed, no rounding) 111 = Shift right (signed, with rounding) 2 SelectInput to barrel shift: 00 = Multiply/Interpolate result 01 = M 10 =Adder/Logic result 11 = L 5 # bits to shift 1 Ceiling of 255 1 Floor of0 (signed data) 12 TOTAL

Adder/Logic 204

The Adder/Logic process block is shown in more detail in FIG. 14 and isdesigned for simple 32-bit addition/subtraction, comparisons, andlogical operations. In a single cycle a single addition, comparison, orlogical operation can be performed, with the result stored in the ALU188's L register 209. There are two primary operands, A and B, which areselected from either of the two crossbars or from the 4 constantregisters. One crossbar selection allows the results of the previouscycle's arithmetic operation to be used while the second provides accessto operands previously calculated by this or another ALU 188. The CPU isthe only unit that has write access to the four constants (K₁-K₄). Incases where an operation such as (A+B)×4 is desired, the direct outputfrom the adder can be used as input to the Barrel Shifter, and can thusbe shifted left 2 places without needing to be latched into the Lregister 209 first. The output from the adder can also be made availableto the multiply unit for a multiply-accumulate operation. The microcodefor the Adder/Logic process block is described in the following table.The interpretations of some bit patterns are deliberately chosen to aiddecoding. Microcode bit interpretation for Adder/Logic unit

# Bits Description 4 0000 = A + B (carry in = 0) 0001 = A + B (carry in= carry out of previous operation) 0010 = A + B + 1 (carry in = 1) 0011= A + 1 (increments A) 0100 = A − B − 1 (carry in = 0) 0101 = A − B(carry in = carry out of previous operation) 0110 = A − B (carry in = 1)0111 = A − 1 (decrements A) 1000 = NOP 1001 = ABS(A − B) 1010 = MIN(A,B) 1011 = MAX(A, B) 1100 = A AND B (both A & B can be inverted, seebelow) 1101 = A OR B (both A & B can be inverted, see below) 1110 = AXOR B (both A & B can be inverted, see below) 1111 = A (A can beinverted, see below) 1 If logical operation: 0 = A = A 1 = A = NOT(A) IfAdder operation: 0 = A is unsigned 1 = A is signed 1 If logicaloperation: 0 = B = B 1 = B = NOT(B) If Adder operation 0 = B is unsigned1 = B is signed 4 Select A [In₁, In₂, Out₁, Out₂, D₀, D₁, D₂, D₃, M, L,S, R, K₁, K₂, K₃, K₄] 4 Select B [In₁, In₂, Out₁, Out₂, D₀, D₁, D₂, D₃,M, L, S, R, K₁, K₂, K₃, K₄] 14 TOTAL

Multiply/Interpolate 205

The Multiply/Interpolate process block is shown in more detail in FIG.15 and is a set of four 8×8 interpolator units that are capable ofperforming four individual 8×8 interpolates per cycle, or can becombined to perform a single 16×16 multiply. This gives the possibilityto perform up to 4 linear interpolations, a single bi-linearinterpolation, or half of a tri-linear interpolation in a single cycle.The result of the interpolations or multiplication is stored in the ALU188's M register 209. There are two primary operands, A and B, which areselected from any of the general registers in the ALU 188 or from fourprogrammable constants internal to the Multiply/Interpolate processblock. Each interpolator block functions as a simple 8 bit interpolator[result=A+(B−A)f] or as a simple 8×8 multiply [result=A*B]. When theoperation is interpolation, A and B are treated as four 8 bit numbers A₀thru A₃ (A₀ is the low order byte), and B₀ thru B₃. Agen, Bgen, and Fgenare responsible for ordering the inputs to the Interpolate units so thatthey match the operation being performed. For example, to performbilinear interpolation, each of the 4 values must be multiplied by adifferent factor & the result summed, while a 16×16 bit multiplicationrequires the factors to be 0. The microcode for the Adder/Logic processblock is described in the following table. Note that the interpretationsof some bit patterns are deliberately chosen to aid decoding.

# Bits Description 4 0000 = (A₁₀ * B₁₀) + V 0001 = (A0 * B0) + (A1 *B1) + V 0010 = (A₁₀ * B₁₀) − V 0011 = V − (A₁₀ * B₁₀) 0100 = InterpolateA₀, B₀ by f₀ 0101 = Interpolate A₀, B₀ by f₀, A₁, B₁ by f₁ 0110 =Interpolate A₀, B₀ by f₀, A₁, B₁ by f₁, A₂, B₂ by f₂ 0111 = InterpolateA₀, B₀ by f₀, A₁, B₁ by f₁, A₂, B₂ by f₂, A₃, B₃ by f₃ 1000 =Interpolate 16 bits stage 1 [M = A₁₀ * f₁₀] 1001 = Interpolate 16 bitsstage 2 [M = M + (A₁₀ * f₁₀)] 1010 = Tri-linear interpolate A by f stage1 [M = A₀f₀ + A₁f₁ + A₂f₂ + A₃f₃] 1011 = Tri-linear interpolate A by fstage 2 [M = M + A₀f₀ + A₁f₁ + A₂f₂ + A₃f₃] 1100 = Bi-linear interpolateA by f stage 1 [M = A₀f₀ + A₁f₁] 1101 = Bi-linear interpolate A by fstage 2 [M = M + A₀f₀ + A₁f₁] 1110 = Bi-linear interpolate A by fcomplete [M = A₀f₀ + A₁f₁ + A₂f₂ + A₃f₃] 1111 = NOP 4 Select A [In₁,In₂, Out₁, Out₂, D₀, D₁, D₂, D₃, M, L, S, R, K₁, K₂, K₃, K₄] 4 Select B[In₁, In₂, Out₁, Out₂, D₀, D₁, D₂, D₃, M, L, S, R, K₁, K₂, K₃, K₄] IfMult: 4 Select V [In₁, In₂, Out₁, Out₂, D₀, D₁, D₂, D₃, K₁, K₂, K₃, K₄,Adder result, M, 0, 1] 1 Treat A as signed 1 Treat B as signed 1 Treat Vas signed If Interp: 4 Select basis for f [In₁, In₂, Out₁, Out₂, D₀, D₁,D₂, D₃, K₁, K₂, K₃, K₄, X, X, X, X] 1 Select interpolation f generationfrom P₁ or P₂ P_(n) is interpreted as # fractional bits in f If P_(n) =0, f is range 0 . . . 255 representing 0 . . . 1 2 Reserved 19 TOTAL

The same 4 bits are used for the selection of V and f, although the last4 options for V don't generally make sense as f values. Interpolatingwith a factor of 1 or 0 is pointless, and the previous multiplication orcurrent result is unlikely to be a meaningful value for f.

I/O Address Generators 189, 190

The I/O Address Generators are shown in more detail in FIG. 16. A VLIWprocess does not access DRAM directly. Access is via 2 I/O AddressGenerators 189, 190, each with its own Input and Output FIFO. A PU e.g.178 reads data from one of two local Input FIFOs, and writes data to oneof two local Output FIFOs. Each I/O Address Generator is responsible forreading data from DRAM and placing it into its Input FIFO, where it canbe read by the PU e.g. 178, and is responsible for taking the data fromits Output FIFO (placed there by the PU e.g. 178) and writing it toDRAM. The I/O Address Generator is a state machine responsible forgenerating addresses and control for data retrieval and storage in DRAMvia the Data cache 76. It is customizable under CPU software control,but cannot be microcoded. The address generator produces addresses intwo broad categories:

-   -   Image Iterators, used to iterate (reading, writing or both)        through pixels of an image in a variety of ways    -   Table I/O, used to randomly access pixels in images, data in        tables, and to simulate FIFOs in DRAM

Each of the I/O Address Generators 189, 190 has its own bus connectionto the Data cache 76, making 2 bus connections per PU e.g. 178, and atotal of 8 buses over the entire VLIW Vector Processor 74. The Datacache 76 is able to service 4 of the maximum 8 requests from the 4 PUse.g. 178 each cycle. The Input and Output FIFOs are 8 entry deep 16-bitwide FIFOs. The various types of address generation (Image Iterators andTable I/O) are described in the subsequent sections.

Registers

The I/O Address Generator has a set of registers for that are used tocontrol address generation. The addressing mode also determines how thedata is formatted and sent into the local Input FIFO, and how data isinterpreted from the local Output FIFO. The CPU is able to access theregisters of the I/O Address Generator via the low speed bus. The firstset of registers define the housekeeping parameters for the I/OGenerator:

Register Name # bits Description Reset 0 A write to this register haltsany operations, and writes 0s to all the data registers of the I/OGenerator. The input and output FIFOs are not cleared. Go 0 A write tothis register restarts the counters according to the current setup. Forexample, if the I/O Generator is a Read Iterator, and the Iterator iscurrently halfway through the image, a write to Go will cause thereading to begin at the start of the image again. While the I/OGenerator is performing, the Active bit of the Status register will beset. Halt 0 A write to this register stops any current activity andclears the Active bit of the Status register. If the Active bit isalready cleared, writing to this register has no effect. Continue 0 Awrite to this register continues the I/O Generator from the currentsetup. Counters are not reset, and FIFOs are not cleared. A write tothis register while the I/O Generator is active has no effect.ClearFIFOsOnGo 1 0 = Don't clear FIFOs on a write to the Go bit. 1 = Doclear FIFOs on a write to the Go bit. Status 8 Status flags

The Status register has the following values

Register Name # bits Description Active 1 0 = Currently inactive 1 =Currently active Reserved 7 —

Caching

Several registers are used to control the caching mechanism, specifyingwhich cache group to use for inputs, outputs etc. See the section on theData cache 76 for more information about cache groups.

Register Name # bits Description CacheGroup1 4 Defines cache group toread data from CacheGroup2 4 Defines which cache group to write data to,and in the case of the ImagePyramidLookup I/O mode, defines the cache touse for reading the Level Information Table.

Image Iterators=Sequential Automatic Access to Pixels

The primary image pixel access method for software and hardwarealgorithms is via Image Iterators. Image iterators perform all of theaddressing and access to the caches of the pixels within an imagechannel and read, write or read & write pixels for their client. ReadIterators read pixels in a specific order for their clients, and WriteIterators write pixels in a specific order for their clients. Clients ofIterators read pixels from the local Input FIFO or write pixels via thelocal Output FIFO.

Read Image Iterators read through an image in a specific order, placingthe pixel data into the local Input FIFO. Every time a client reads apixel from the Input FIFO, the Read Iterator places the next pixel fromthe image (via the Data cache 76) into the FIFO.

Write Image Iterators write pixels in a specific order to write out theentire image. Clients write pixels to the Output FIFO that is in turnread by the Write Image Iterator and written to DRAM via the Data cache76.

Typically a VLIW process will have its input tied to a Read Iterator,and output tied to a corresponding Write Iterator. From the PU e.g. 178microcode program's perspective, the FIFO is the effective interface toDRAM. The actual method of carrying out the storage (apart from thelogical ordering of the data) is not of concern. Although the FIFO isperceived to be effectively unlimited in length, in practice the FIFO isof limited length, and there can be delays storing and retrieving data,especially if several memory accesses are competing. A variety of ImageIterators exist to cope with the most common addressing requirements ofimage processing algorithms. In most cases there is a correspondingWrite Iterator for each Read Iterator. The different Iterators arelisted in the following table:

Read Iterators Write Iterators Sequential Read Sequential Write Box Read— Vertical Strip Read Vertical Strip Write

The 4 bit Address Mode Register is used to determine the Iterator type:

Bit # Address Mode 3 0 = This addressing mode is an Iterator 2 to 0Iterator Mode 001 = Sequential Iterator 010 = Box [read only] 100 =Vertical Strip remaining bit patterns are reserved

The Access Specific registers are used as follows:

Register Name LocalName Description AccessSpecific₁ Flags Flags used forreading and writing AccessSpecific₂ XBoxSize Determines the size in X ofBox Read. Valid values are 3, 5, and 7. AccessSpecific₃ YBoxSizeDetermines the size in Y of Box Read. Valid values are 3, 5, and 7.AccessSpecific₄ BoxOffset Offset between one pixel center and the nextduring a Box Read only. Usual value is 1, but other useful valuesinclude 2, 4, 8 . . . See Box Read for more details.

The Flags register (AccessSpecific₁) contains a number of flags used todetermine factors affecting the reading and writing of data. The Flagsregister has the following composition:

Label #bits Description ReadEnable 1 Read data from DRAM WriteEnable 1Write data to DRAM [not valid for Box mode] PassX 1 Pass X (pixel)ordinate back to Input FIFO PassY 1 Pass Y (row) ordinate back to InputFIFO Loop 1 0 = Do not loop through data 1 = Loop through data Reserved11 Must be 0

Notes on ReadEnable and WriteEnable:

-   -   When ReadEnable is set, the I/O Address Generator acts as a Read        Iterator, and therefore reads the image in a particular order,        placing the pixels into the Input FIFO.    -   When WriteEnable is set, the I/O Address Generator acts as a        Write Iterator, and therefore writes the image in a particular        order, taking the pixels from the Output FIFO.    -   When both ReadEnable and WriteEnable are set, the I/O Address        Generator acts as a Read Iterator and as a Write Iterator,        reading pixels into the Input FIFO, and writing pixels from the        Output FIFO. Pixels are only written after they have been        read—i.e. the Write Iterator will never go faster than the Read        Iterator. Whenever this mode is used, care should be taken to        ensure balance between in and out processing by the VLIW        microcode. Note that separate cache groups can be specified on        reads and writes by loading different values in CacheGroup1 and        CacheGroup2.

Notes on PassX and PassY:

-   -   If PassX and PassY are both set, the Y ordinate is placed into        the Input FIFO before the X ordinate.    -   PassX and PassY are only intended to be set when the ReadEnable        bit is clear. Instead of passing the ordinates to the address        generator, the ordinates are placed directly into the Input        FIFO. The ordinates advance as they are removed from the FIFO.    -   If WriteEnable bit is set, the VLIW program must ensure that it        balances reads of ordinates from the Input FIFO with writes to        the Output FIFO, as writes will only occur up to the ordinates        (see note on ReadEnable and WriteEnable above).

Notes on Loop:

-   -   If the Loop bit is set, reads will recommence at [StartPixel,        StartRow] once it has reached [EndPixel, EndRow]. This is ideal        for processing a structure such a convolution kernel or a dither        cell matrix, where the data must be read repeatedly.    -   Looping with ReadEnable and WriteEnable set can be useful in an        environment keeping a single line history, but only where it is        useful to have reading occur before writing. For a FIFO effect        (where writing occurs before reading in a length constrained        fashion), use an appropriate Table I/O addressing mode instead        of an Image Iterator.    -   Looping with only WriteEnable set creates a written window of        the last N pixels. This can be used with an asynchronous process        that reads the data from the window. The Artcard Reading        algorithm makes use of this mode.

Sequential Read and Write Iterators

FIG. 17 illustrates the pixel data format. The simplest Image Iteratorsare the Sequential Read Iterator and corresponding Sequential WriteIterator. The Sequential Read Iterator presents the pixels from achannel one line at a time from top to bottom, and within a line, pixelsare presented left to right. The padding bytes are not presented to theclient. It is most useful for algorithms that must perform some processon each pixel from an image but don't care about the order of the pixelsbeing processed, or want the data specifically in this order.Complementing the Sequential Read Iterator is the Sequential WriteIterator. Clients write pixels to the Output FIFO. A Sequential WriteIterator subsequently writes out a valid image using appropriate cachingand appropriate padding bytes. Each Sequential Iterator requires accessto 2 cache lines. When reading, while 32 pixels are presented from onecache line, the other cache line can be loaded from memory. Whenwriting, while 32 pixels are being filled up in one cache line, theother can be being written to memory. A process that performs anoperation on each pixel of an image independently would typically use aSequential Read Iterator to obtain pixels, and a Sequential WriteIterator to write the new pixel values to their corresponding locationswithin the destination image. Such a process is shown in FIG. 18.

In most cases, the source and destination images are different, and arerepresented by 2 I/O Address Generators 189, 190. However it can bevalid to have the source image and destination image to be the same,since a given input pixel is not read more than once. In that case, thenthe same Iterator can be used for both input and output, with both theReadEnable and WriteEnable registers set appropriately. For maximumefficiency, 2 different cache groups should be used—one for reading andthe other for writing. If data is being created by a VLIW process to bewritten via a Sequential Write Iterator, the PassX and PassY flags canbe used to generate coordinates that are then passed down the InputFIFO. The VLIW process can use these coordinates and create the outputdata appropriately.

Box Read Iterator

The Box Read Iterator is used to present pixels in an order most usefulfor performing operations such as general-purpose filters and convolve.The Iterator presents pixel values in a square box around thesequentially read pixels. The box is limited to being 1, 3, 5, or 7pixels wide in X and Y (set XBoxSize and YBoxSize—they must be the samevalue or 1 in one dimension and 3, 5, or 7 in the other). The process isshown in FIG. 19:

BoxOffset: This special purpose register is used to determine asub-sampling in terms of which input pixels will be used as the centerof the box. The usual value is 1, which means that each pixel is used asthe center of the box. The value “2” would be useful in scaling an imagedown by 4:1 as in the case of building an image pyramid. Using pixeladdresses from the previous diagram, the box would be centered on pixel0, then 2, 8, and 10. The Box Read Iterator requires access to a maximumof 14 (2×7) cache lines. While pixels are presented from one set of 7lines, the other cache lines can be loaded from memory.

Box Write Iterator

There is no corresponding Box Write Iterator, since the duplication ofpixels is only required on input. A process that uses the Box ReadIterator for input would most likely use the Sequential Write Iteratorfor output since they are in sync. A good example is the convolver,where N input pixels are read to calculate 1 output pixel. The processflow is as illustrated in FIG. 20. The source and destination imagesshould not occupy the same memory when using a Box Read Iterator, assubsequent lines of an image require the original (not newly calculated)values.

Vertical-Strip Read and Write Iterators

In some instances it is necessary to write an image in output pixelorder, but there is no knowledge about the direction of coherence ininput pixels in relation to output pixels. An example of this isrotation. If an image is rotated 90 degrees, and we process the outputpixels horizontally, there is a complete loss of cache coherence. On theother hand, if we process the output image one cache line's width ofpixels at a time and then advance to the next line (rather than advanceto the next cache-line's worth of pixels on the same line), we will gaincache coherence for our input image pixels. It can also be the case thatthere is known ‘block’ coherence in the input pixels (such as colorcoherence), in which case the read governs the processing order, and thewrite, to be synchronized, must follow the same pixel order.

The order of pixels presented as input (Vertical-Strip Read), orexpected for output (Vertical-Strip Write) is the same. The order ispixels 0 to 31 from line 0, then pixels 0 to 31 of line 1 etc for alllines of the image, then pixels 32 to 63 of line 0, pixels 32 to 63 ofline 1 etc. In the final vertical strip there may not be exactly 32pixels wide. In this case only the actual pixels in the image arepresented or expected as input. This process is illustrated in FIG. 21.process that requires only a Vertical-Strip Write Iterator willtypically have a way of mapping input pixel coordinates given an outputpixel coordinate. It would access the input image pixels according tothis mapping, and coherence is determined by having sufficient cachelines on the ‘random-access’ reader for the input image. The coordinateswill typically be generated by setting the PassX and PassY flags on theVerticalStripWrite Iterator, as shown in the process overviewillustrated in FIG. 22.

It is not meaningful to pair a Write Iterator with a Sequential ReadIterator or a Box read Iterator, but a Vertical-Strip Write Iteratordoes give significant improvements in performance when there is a nontrivial mapping between input and output coordinates.

It can be meaningful to pair a Vertical Strip Read Iterator and VerticalStrip Write Iterator. In this case it is possible to assign both to asingle ALU 188 if input and output images are the same. If coordinatesare required, a further Iterator must be used with PassX and PassY flagsset. The Vertical Strip Read/Write Iterator presents pixels to the InputFIFO, and accepts output pixels from the Output FIFO. Appropriatepadding bytes will be inserted on the write. Input and output require aminimum of 2 cache lines each for good performance.

Table I/O Addressing Modes

It is often necessary to lookup values in a table (such as an image).Table I/O addressing modes provide this functionality, requiring theclient to place the index/es into the Output FIFO. The I/O AddressGenerator then processes the index/es, looks up the data appropriately,and returns the looked-up values in the Input FIFO for subsequentprocessing by the VLIW client.

1D, 2D and 3D tables are supported, with particular modes targeted atinterpolation. To reduce complexity on the VLIW client side, the indexvalues are treated as fixed-point numbers, with AccessSpecific registersdefining the fixed point and therefore which bits should be treated asthe integer portion of the index. Data formats are restricted forms ofthe general Image Characteristics in that the PixelOffset register isignored, the data is assumed to be contiguous within a row, and can onlybe 8 or 16 bits (1 or 2 bytes) per data element. The 4 bit Address ModeRegister is used to determine the I/O type:

Bit # Address Mode 3 1 = This addressing mode is Table I/O 2 to 0 000 =1D Direct Lookup 001 = 1D Interpolate (linear) 010 = DRAM FIFO 011 =Reserved 100 = 2D Interpolate (bi-linear) 101 = Reserved 110 = 3DInterpolate (tri-linear) 111 = Image Pyramid Lookup

The access specific registers are:

Register Name LocalName #bits Description AccessSpecific₁ Flags 8General flags for reading and writing. See below for more information.AccessSpecific₂ FractX 8 Number of fractional bits in X indexAccessSpecific₃ FractY 8 Number of fractional bits in Y indexAccessSpecific₄ FractZ 8 Number of fractional bits in Z index (low 8bits/next ZOffset 12 or See below 12 or 24 bits)) 24

FractX, FractY, and FractZ are used to generate addresses based onindexes, and interpret the format of the index in terms of significantbits and integer/fractional components. The various parameters are onlydefined as required by the number of dimensions in the table beingindexed. A 1D table only needs FractX, a 2D table requires FractX andFractY. Each Fract_value consists of the number of fractional bits inthe corresponding index. For example, an X index may be in the format5:3. This would indicate 5 bits of integer, and 3 bits of fraction.FractX would therefore be set to 3. A simple 1D lookup could have theformat 8:0, i.e. no fractional component at all. FractX would thereforebe 0. ZOffset is only required for 3D lookup and takes on two differentinterpretations. It is described more fully in the 3D-table lookupsection. The Flags register (AccessSpecific₁) contains a number of flagsused to determine factors affecting the reading (and in one case,writing) of data. The Flags register has the following composition:

Label #bits Description ReadEnable 1 Read data from DRAM WriteEnable 1Write data to DRAM [only valid for 1D direct lookup] DataSize 1 0 = 8bit data 1 = 16 bit data Reserved 5 Must be 0

With the exception of the 1D Direct Lookup and DRAM FIFO, all Table I/Omodes only support reading, and not writing. Therefore the ReadEnablebit will be set and the WriteEnable bit will be clear for all I/O modesother than these two modes. The 1D Direct Lookup supports 3 modes:

-   -   Read only, where the ReadEnable bit is set and the WriteEnable        bit is clear    -   Write only, where the ReadEnable bit is clear and the        WriteEnable bit is clear    -   Read-Modify-Write, where both ReadEnable and the WriteEnable        bits are set

The different modes are described in the 1D Direct Lookup section below.The DRAM FIFO mode supports only 1 mode:

-   -   Write-Read mode, where both ReadEnable and the WriteEnable bits        are set

This mode is described in the DRAM FIFO section below. The DataSize flagdetermines whether the size of each data elements of the table is 8 or16 bits. Only the two data sizes are supported. 32 bit elements can becreated in either of 2 ways depending on the requirements of theprocess:

-   -   Reading from 2 16-bit tables simultaneously and combining the        result. This is convenient if timing is an issue, but has the        disadvantage of consuming 2 I/O Address Generators 189, 190, and        each 32-bit element is not readable by the CPU as a 32-bit        entity.    -   Reading from a 16-bit table twice and combining the result. This        is convenient since only 1 lookup is used, although different        indexes must be generated and passed into the lookup.

1 Dimensional Structures Direct Lookup

A direct lookup is a simple indexing into a 1 dimensional lookup table.Clients can choose between 3 access modes by setting appropriate bits inthe Flags register:

-   -   Read only    -   Write only    -   Read-Modify-Write

Read Only

A client passes the fixed-point index X into the Output FIFO, and the 8or 16-bit value at Table[Int(X)] is returned in the Input FIFO. Thefractional component of the index is completely ignored. If the index isout of bounds, the DuplicateEdge flag determines whether the edge pixelor ConstantPixel is returned. The address generation is straightforward:

-   -   If DataSize indicates 8 bits, X is barrel-shifted right FractX        bits, and the result is added to the table's base address        ImageStart.    -   If DataSize indicates 16 bits, X is barrel-shifted right FractX        bits, and the result shifted left 1 bit (bit0 becomes 0) is        added to the table's base address ImageStart.

The 8 or 16-bit data value at the resultant address is placed into theInput FIFO. Address generation takes 1 cycle, and transferring therequested data from the cache to the Output FIFO also takes 1 cycle(assuming a cache hit). For example, assume we are looking up values ina 256-entry table, where each entry is 16 bits, and the index is a 12bit fixed-point format of 8:4. FractX should be 4, and DataSize 1. Whenan index is passed to the lookup, we shift right 4 bits, then add theresult shifted left 1 bit to ImageStart.

Write Only

A client passes the fixed-point index X into the Output FIFO followed bythe 8 or 16-bit value that is to be written to the specified location inthe table. A complete transfer takes a minimum of 2 cycles. 1 cycle foraddress generation, and 1 cycle to transfer the data from the FIFO toDRAM. There can be an arbitrary number of cycles between a VLIW processplacing the index into the FIFO and placing the value to be written intothe FIFO. Address generation occurs in the same way as Read Only mode,but instead of the data being read from the address, the data from theOutput FIFO is written to the address. If the address is outside thetable range, the data is removed from the FIFO but not written to DRAM.

Read-Modify-Write

A client passes the fixed-point index X into the Output FIFO, and the 8or 16-bit value at Table[Int(X)] is returned in the Input FIFO. The nextvalue placed into the Output FIFO is then written to Table[Int(X)],replacing the value that had been returned earlier. The generalprocessing loop then, is that a process reads from a location, modifiesthe value, and writes it back. The overall time is 4 cycles:

-   -   Generate address from index    -   Return value from table    -   Modify value in some way    -   Write it back to the table

There is no specific read/write mode where a client passes in a flagsaying “read from X” or “write to X”. Clients can simulate a “read fromX” by writing the original value, and a “write to X” by simply ignoringthe returned value. However such use of the mode is not encouraged sinceeach action consumes a minimum of 3 cycles (the modify is not required)and 2 data accesses instead of 1 access as provided by the specific Readand Write modes.

Interpolate Table

This is the same as a Direct Lookup in Read mode except that two valuesare returned for a given fixed-point index X instead of one. The valuesreturned are Table[Int(X)], and Table[Int(X)+1]. If either index is outof bounds the DuplicateEdge flag determines whether the edge pixel orConstantPixel is returned. Address generation is the same as DirectLookup, with the exception that the second address is simply Address1+1or 2 depending on 8 or 16 bit data. Transferring the requested data tothe Output FIFO takes 2 cycles (assuming a cache hit), although two8-bit values may actually be returned from the cache to the AddressGenerator in a single 16-bit fetch.

DRAM FIFO

A special case of a read/write 1D table is a DRAM FIFO. It is oftennecessary to have a simulated FIFO of a given length using DRAM andassociated caches. With a DRAM FIFO, clients do not index explicitlyinto the table, but write to the Output FIFO as if it was one end of aFIFO and read from the Input FIFO as if it was the other end of the samelogical FIFO. 2 counters keep track of input and output positions in thesimulated FIFO, and cache to DRAM as needed. Clients need to set bothReadEnable and WriteEnable bits in the Flags register.

An example use of a DRAM FIFO is keeping a single line history of somevalue. The initial history is written before processing begins. As thegeneral process goes through a line, the previous line's value isretrieved from the FIFO, and this line's value is placed into the FIFO(this line will be the previous line when we process the next line). Solong as input and outputs match each other on average, the Output FIFOshould always be full. Consequently there is effectively no access delayfor this kind of FIFO (unless the total FIFO length is very small—say 3or 4 bytes, but that would defeat the purpose of the FIFO).

2 Dimensional Tables Direct Lookup

A 2 dimensional direct lookup is not supported. Since all cases of 2Dlookups are expected to be accessed for bi-linear interpolation, aspecial bi-linear lookup has been implemented.

Bi-Linear lookup

This kind of lookup is necessary for bi-linear interpolation of datafrom a 2D table. Given fixed-point X and Y coordinates (placed into theOutput FIFO in the order Y, X), 4 values are returned after lookup. Thevalues (in order) are:

-   -   Table[Int(X), Int(Y)]    -   Table[Int(X)+1, Int(Y)]    -   Table[Int(X), Int(Y)+1]    -   Table[Int(X)+1, Int(Y)+1]

The order of values returned gives the best cache coherence. If the datais 8-bit, 2 values are returned each cycle over 2 cycles with the loworder byte being the first data element. If the data is 16-bit, the 4values are returned in 4 cycles, 1 entry per cycle. Address generationtakes 2 cycles. The first cycle has the index (Y) barrel-shifted rightFractY bits being multiplied by RowOffset, with the result added toImageStart. The second cycle shifts the X index right by FractX bits,and then either the result (in the case of 8 bit data) or the resultshifted left 1 bit (in the case of 16 bit data) is added to the resultfrom the first cycle. This gives us address Adr=address of Table[Int(X),Int(Y)]:

Adr = ImageStart + ShiftRight(Y, FractY) * RowOffset) + ShiftRight(X, FractX)

We keep a copy of Adr in AdrOld for use fetching subsequent entries.

-   -   If the data is 8 bits, the timing is 2 cycles of address        generation, followed by 2 cycles of data being returned (2 table        entries per cycle).    -   If the data is 16 bits, the timing is 2 cycles of address        generation, followed by 4 cycles of data being returned (1 entry        per cycle)

The following 2 tables show the method of address calculation for 8 and16 bit data sizes:

Cycle Calculation while fetching 2 x 8-bit data entries from Adr 1 Adr =Adr + RowOffset 2 <preparing next lookup> Cycle Calculation whilefetching 1 x 16-bit data entry from Adr 1 Adr = Adr + 2 2 Adr = AdrOld +RowOffset 3 Adr = Adr + 2 4 <preparing next lookup>

In both cases, the first cycle of address generation can overlap theinsertion of the X index into the FIFO, so the effective timing can beas low as 1 cycle for address generation, and 4 cycles of return data.If the generation of indexes is 2 steps ahead of the results, then thereis no effective address generation time, and the data is simply producedat the appropriate rate (2 or 4 cycles per set).

3 Dimensional Lookup Direct Lookup

Since all cases of 2D lookups are expected to be accessed for tri-linearinterpolation, two special tri-m linear lookups have been implemented.The first is a straightforward lookup table, while the second is fortri-linear interpolation from an Image Pyramid.

Tri-Linear Lookup

This type of lookup is useful for 3D tables of data, such as colorconversion tables. The standard image parameters define a single XYplane of the data—i.e. each plane consists of ImageHeight rows, each rowcontaining RowOffset bytes. In most circumstances, assuming contiguousplanes, one XY plane will be ImageHeight×RowOffset bytes after another.Rather than assume or calculate this offset, the software via the CPUmust provide it in the form of a 12-bit ZOffset register. In this formof lookup, given 3 fixed-point indexes in the order Z, Y, X, 8 valuesare returned in order from the lookup table:

-   -   Table[Int(X), Int(Y), Int(Z)]    -   Table[Int(X)+1, Int(Y), Int(Z)]    -   Table[Int(X), Int(Y)+1, Int(Z)]    -   Table[Int(X)+1, Int(Y)+1, Int(Z)]    -   Table[Int(X), Int(Y), Int(Z)+1]    -   Table[Int(X)+1, Int(Y), Int(Z)+1]    -   Table[Int(X), Int(Y)+1, Int(Z)+1]    -   Table[Int(X)+1, Int(Y)+1, Int(Z)+1]

The order of values returned gives the best cache coherence. If the datais 8-bit, 2 values are returned each cycle over 4 cycles with the loworder byte being the first data element. If the data is 16-bit, the 4values are returned in 8 cycles, 1 entry per cycle. Address generationtakes 3 cycles. The first cycle has the index (Z) barrel-shifted rightFractZ bits being multiplied by the 12-bit ZOffset and added toImageStart. The second cycle has the index (Y) barrel-shifted rightFractY bits being multiplied by RowOffset, with the result added to theresult of the previous cycle. The second cycle shifts the X index rightby FractX bits, and then either the result (in the case of 8 bit data)or the result shifted left 1 bit (in the case of 16 bit data) is addedto the result from the second cycle. This gives us address Adr=addressof Table[Int(X), Int(Y), Int(Z)]:

Adr = ImageStart + (ShiftRight(Z, FractZ) * ZOffset) + (ShiftRight(Y, FractY) * RowOffset) + ShiftRight(X, FractX)

We keep a copy of Adr in AdrOld for use fetching subsequent entries.

-   -   If the data is 8 bits, the timing is 2 cycles of address        generation, followed by 2 cycles of data being returned (2 table        entries per cycle).    -   If the data is 16 bits, the timing is 2 cycles of address        generation, followed by 4 cycles of data being returned (1 entry        per cycle)

The following 2 tables show the method of address calculation for 8 and16 bit data sizes:

Cycle Calculation while fetching 2 x 8-bit data entries from Adr 1 Adr =Adr + RowOffset 2 Adr = AdrOld + ZOffset 3 Adr = Adr + RowOffset 4<preparing next lookup> Cycle Calculation while fetching 1 x 16-bit dataentries from Adr 1 Adr = Adr + 2 2 Adr = AdrOld + RowOffset 3 Adr =Adr + 2 4 Adr, AdrOld = AdrOld + Zoffset 5 Adr = Adr + 2 6 Adr =AdrOld + RowOffset 7 Adr = Adr + 2 8 <preparing next lookup>

In both cases, the cycles of address generation can overlap theinsertion of the indexes into the FIFO, so the effective timing for asingle one-off lookup can be as low as 1 cycle for address generation,and 4 cycles of return data. If the generation of indexes is 2 stepsahead of the results, then there is no effective address generationtime, and the data is simply produced at the appropriate rate (4 or 8cycles per set).

Image Pyramid Lookup

During brushing, tiling, and warping it is necessary to compute theaverage color of a particular area in an image. Rather than calculatethe value for each area given, these functions make use of an imagepyramid. The description and construction of an image pyramid isdetailed in the section on Internal Image Formats in the DRAM interface81 chapter of this document. This section is concerned with a method ofaddressing given pixels in the pyramid in terms of 3 fixed-point indexesordered: level (Z), Y, and X. Note that Image Pyramid lookup assumes 8bit data entries, so the DataSize flag is completely ignored. Afterspecification of Z, Y, and X, the following 8 pixels are returned viathe Input FIFO:

-   -   The pixel at [Int(X), Int(Y)], level Int(Z)    -   The pixel at [Int(X)+1, Int(Y)], level Int(Z)    -   The pixel at [Int(X), Int(Y)+1], level Int(Z)    -   The pixel at [Int(X)+1, Int(Y)+1], level Int(Z)    -   The pixel at [Int(X), Int(Y)], level Int(Z)+1    -   The pixel at [Int(X)+1, Int(Y)], level Int(Z)+1    -   The pixel at [Int(X), Int(Y)+1], level Int(Z)+1    -   The pixel at [Int(X)+1, Int(Y)+1], level Int(Z)+1

The 8 pixels are returned as 4×16 bit entries, with X and X+1 entriescombined hi/lo. For example, if the scaled (X, Y) coordinate was (10.4,12.7) the first 4 pixels returned would be: (10, 12), (11, 12), (10, 13)and (11, 13). When a coordinate is outside the valid range, clients havethe choice of edge pixel duplication or returning of a constant colorvalue via the DuplicateEdgePixels and ConstantPixel registers (only thelow 8 bits are used). When the Image Pyramid has been constructed, thereis a simple mapping from level 0 coordinates to level Z coordinates. Themethod is simply to shift the X or Y coordinate right by Z bits. Thismust be done in addition to the number of bits already shifted toretrieve the integer portion of the coordinate (i.e. shifting rightFractX and FractY bits for X and Y ordinates respectively). To find theImageStart and RowOffset value for a given level of the image pyramid,the 24-bit ZOffset register is used as a pointer to a Level InformationTable. The table is an array of records, each representing a given levelof the pyramid, ordered by level number. Each record consists of a16-bit offset ZOffset from ImageStart to that level of the pyramid(64-byte aligned address as lower 6 bits of the offset are not present),and a 12 bit ZRowOffset for that level. Element 0 of the table wouldcontain a ZOffset of 0, and a ZRowOffset equal to the general registerRowOffset, as it simply points to the full sized image. The ZOffsetvalue at element N of the table should be added to ImageStart to yieldthe effective ImageStart of level N of the image pyramid. The RowOffsetvalue in element N of the table contains the RowOffset value for levelN. The software running on the CPU must set up the table appropriatelybefore using this addressing mode. The actual address generation isoutlined here in a cycle by cycle description:

Load From Cycle Register Address Other Operations 0 — — ZAdr =ShiftRight(Z, FractZ) + ZOffset ZInt = ShiftRight(Z, FractZ) 1 ZOffsetZadr ZAdr += 2 YInt = ShiftRight(Y, FractY) 2 ZRowOffset ZAdr ZAdr += 2YInt = ShiftRight(YInt, ZInt) Adr = ZOffset + ImageStart 3 ZOffset ZAdrZAdr += 2 Adr += ZrowOffset * YInt XInt = ShiftRight(X, FractX) 4 ZAdrZAdr Adr += ShiftRight(XInt, ZInt) ZOffset += ShiftRight(XInt, 1) 5 FIFOAdr Adr += ZrowOffset ZOffset += ImageStart 6 FIFO Adr Adr = (ZAdr *ShiftRight(Yint, 1)) + ZOffset 7 FIFO Adr Adr += Zadr 8 FIFO Adr < Cycle0 for next retrieval>

The address generation as described can be achieved using a singleBarrel Shifter, 2 adders, and a single 16×16 multiply/add unit yielding24 bits. Although some cycles have 2 shifts, they are either the sameshift value (i.e. the output of the Barrel Shifter is used two times) orthe shift is 1 bit, and can be hard wired. The following internalregisters are required: ZAdr, Adr, ZInt, YInt, XInt, ZRowOffset, andZImageStart. The Int registers only need to be 8 bits maximum, while theothers can be up to 24 bits. Since this access method only reads from,and does not write to image pyramids, the CacheGroup2 is used to lookupthe Image Pyramid Address Table (via ZAdr). CacheGroup1 is used forlookups to the image pyramid itself (via Adr). The address table isaround 22 entries (depending on original image size), each of 4 bytes.Therefore 3 or 4 cache lines should be allocated to CacheGroup2, whileas many cache lines as possible should be allocated to CacheGroup1. Thetiming is 8 cycles for returning a set of data, assuming that Cycle 8and Cycle 0 overlap in operation—i.e. the next request's Cycle 0 occursduring Cycle 8. This is acceptable since Cycle 0 has no memory access,and Cycle 8 has no specific operations.

Generation of Coordinates Using VLIW Vector Processor 74

Some functions that are linked to Write Iterators require the X and/or Ycoordinates of the current pixel being processed in part of theprocessing pipeline. Particular processing may also need to take placeat the end of each row, or column being processed. In most cases, thePassX and PassY flags should be sufficient to completely generate allcoordinates. However, if there are special requirements, the followingfunctions can be used. The calculation can be spread over a number ofALUs, for a single cycle generation, or be in a single ALU 188 for amulti-cycle generation.

Generate Sequential [X, Y]

When a process is processing pixels in sequential order according to theSequential Read Iterator (or generating pixels and writing them out to aSequential Write Iterator), the following process can be used togenerate X, Y coordinates instead of PassX/PassY flags as shown in FIG.23.

The coordinate generator counts up to ImageWidth in the X ordinate, andonce per ImageWidth pixels increments the Y ordinate. The actual processis illustrated in FIG. 24, where the following constants are set bysoftware:

Constant Value K₁ ImageWidth K₂ ImageHeight (optional)

The following registers are used to hold temporary variables:

Variable Value Reg₁ X (starts at 0 each line) Reg₂ Y (starts at 0)

The requirements are summarized as follows:

Requirements *+ + R K LU Iterators General 0 ¾ 2 ½ 0 0 TOTAL 0 ¾ 2 ½ 0 0

Generate Vertical Strip [X, Y]

When a process is processing pixels in order to write them to a VerticalStrip Write Iterator, and for some reason cannot use the PassX/PassYflags, the process as illustrated in FIG. 25 can be used to generate X,Y coordinates. The coordinate generator simply counts up to ImageWidthin the X ordinate, and once per ImageWidth pixels increments the Yordinate. The actual process is illustrated in FIG. 26, where thefollowing constants are set by software:

Constant Value K₁ 32 K₂ ImageWidth K₃ ImageHeight

The following registers are used to hold temporary variables:

Variable Value Reg₁ StartX (starts at 0, and is incremented by 32 onceper vertical strip) Reg₂ X Reg₃ EndX (starts at 32 and is incremented by32 to a maximum of ImageWidth) once per vertical strip) Reg₄ Y

The requirements are summarized as follows:

Requirements *+ + R K LU Iterators General 0 4 4 3 0 0 TOTAL 0 4 4 3 0 0

The calculations that occur once per vertical strip (2 additions, one ofwhich has an associated MIN) are not included in the general timingstatistics because they are not really part of the per pixel timing.However they do need to be taken into account for the programming of themicrocode for the particular function.

Image Sensor Interface (ISI 83)

The Image Sensor Interface (ISI 83) takes data from the CMOS ImageSensor and makes it available for storage in DRAM. The image sensor hasan aspect ratio of 3:2, with a typical resolution of 750×500 samples,yielding 375K (8 bits per pixel). Each 2×2 pixel block has theconfiguration as shown in FIG. 27. The ISI 83 is a state machine thatsends control information to the Image Sensor, including frame syncpulses and pixel clock pulses in order to read the image. Pixels areread from the image sensor and placed into the VLIW Input FIFO 78. TheVLIW is then able to process and/or store the pixels. This isillustrated further in FIG. 28. The ISI 83 is used in conjunction with aVLIW program that stores the sensed Photo Image in DRAM. Processingoccurs in 2 steps:

-   -   A small VLIW program reads the pixels from the FIFO and writes        them to DRAM via a Sequential Write Iterator.    -   The Photo Image in DRAM is rotated 90, 180 or 270 degrees        according to the orientation of the camera when the photo was        taken.

If the rotation is 0 degrees, then step 1 merely writes the Photo Imageout to the final Photo Image location and step 2 is not performed. Ifthe rotation is other than 0 degrees, the image is written out to atemporary area (for example into the Print Image memory area), and thenrotated during step 2 into the final Photo Image location. Step 1 isvery simple microcode, taking data from the VLIW Input FIFO 78 andwriting it to a Sequential Write Iterator. Step 2's rotation isaccomplished by using the accelerated Vark Affine Transform function.The processing is performed in 2 steps in order to reduce designcomplexity and to re-use the Vark affine transform rotate logic alreadyrequired for images. This is acceptable since both steps are completedin approximately 0.03 seconds, a time imperceptible to the operator ofthe Artcam. Even so, the read process is sensor speed bound, taking 0.02seconds to read the full frame, and approximately 0.01 seconds to rotatethe image.

The orientation is important for converting between the sensed PhotoImage and the internal format image, since the relative positioning ofR, G, and B pixels changes with orientation. The processed image mayalso have to be rotated during the Print process in order to be in thecorrect orientation for printing. The 3D model of the Artcam has 2 imagesensors, with their inputs multiplexed to a single ISI 83 (differentmicrocode, but same ACP 31). Since each sensor is a frame store, bothimages can be taken simultaneously, and then transferred to memory oneat a time.

Display Controller 88

When the “Take” button on an Artcam is half depressed, the TFT willdisplay the current image from the image sensor (converted via a simpleVLIW process). Once the Take button is fully depressed, the Taken Imageis displayed. When the user presses the Print button and imageprocessing begins, the TFT is turned off. Once the image has beenprinted the TFT is turned on again. The Display Controller 88 is used inthose Artcam models that incorporate a flat panel display. An exampledisplay is a TFT LCD of resolution 240×160 pixels. The structure of theDisplay Controller 88 is illustrated in FIG. 29. The Display Controller88 State Machine contains registers that control the timing of the SyncGeneration, where the display image is to be taken from (in DRAM via theData cache 76 via a specific Cache Group), and whether the TFT should beactive or not (via TFT Enable) at the moment. The CPU can write to theseregisters via the low speed bus. Displaying a 240×160 pixel image on anRGB TFT requires 3 components per pixel. The image taken from DRAM isdisplayed via 3 DACs, one for each of the R, G, and B output signals. Atan image refresh rate of 30 frames per second (60 fields per second) theDisplay Controller 88 requires data transfer rates of:

240×160×3×30=3.5 MB per second

This data rate is low compared to the rest of the system. However it ishigh enough to cause VLIW programs to slow down during the intensiveimage processing. The general principles of TFT operation should reflectthis.

Image Data Formats

As stated previously, the DRAM Interface 81 is responsible forinterfacing between other client portions of the ACP chip and theRAIVIBUS DRAM. In effect, each module within the DRAM Interface is anaddress generator.

There are three logical types of images manipulated by the ACP. Theyare:

-   -   CCD Image, which is the Input Image captured from the CCD.    -   Internal Image format—the Image format utilised internally by        the Artcam device.    -   Print Image—the Output Image format printed by the Artcam

These images are typically different in color space, resolution, and theoutput & input color spaces which can vary from camera to camera. Forexample, a CCD image on a low-end camera may be a different resolution,or have different color characteristics from that used in a high-endcamera. However all internal image formats are the same format in termsof color space across all cameras.

In addition, the three image types can vary with respect to whichdirection is ‘up’. The physical orientation of the camera causes thenotion of a portrait or landscape image, and this must be maintainedthroughout processing. For this reason, the internal image is alwaysoriented correctly, and rotation is performed on images obtained fromthe CCD and during the print operation.

CCD Image Organization

Although many different CCD image sensors could be utilised, it will beassumed that the CCD itself is a 750×500 image sensor, yielding 375,000bytes (8 bits per pixel). Each 2×2 pixel block having the configurationas depicted in FIG. 30.

A CCD Image as stored in DRAM has consecutive pixels with a given linecontiguous in memory. Each line is stored one after the other. The imagesensor Interface 83 is responsible for taking data from the CCD andstoring it in the DRAM correctly oriented. Thus a CCD image withrotation 0 degrees has its first line G, R, G, R, G, R . . . and itssecond line as B, G, B, G, B, G . . . . If the CCD image should beportrait, rotated 90 degrees, the first line will be R, G, R, G, R, Gand the second line G, B, G, B, G, B . . . etc.

Pixels are stored in an interleaved fashion since all color componentsare required in order to convert to the internal image format.

It should be noted that the ACP 31 makes no assumptions about the CCDpixel format, since the actual CCDs for imaging may vary from Artcam toArtcam, and over time. All processing that takes place via the hardwareis controlled by major microcode in an attempt to extend the usefulnessof the ACP 31.

Internal Image Organization

Internal images typically consist of a number of channels. Vark imagescan include, but are not limited to:

Lab

Labα

LabΔ

αΔ

L

L, a and b correspond to components of the Lab color space, α is a mattechannel (used for compositing), and Δ is a bump-map channel (used duringbrushing, tiling and illuminating).

The VLIW processor 74 requires images to be organized in a planarconfiguration. Thus a Lab image would be stored as 3 separate blocks ofmemory:

one block for the L channel,

one block for the a channel, and

one block for the b channel

Within each channel block, pixels are stored contiguously for a givenrow (plus some optional padding bytes), and rows are stored one afterthe other.

Turning to FIG. 31 there is illustrated an example form of storage of alogical image 100. The logical image 100 is stored in a planar fashionhaving L 101, a 102 and b 103 color components stored one after another.Alternatively, the logical image 100 can be stored in a compressedformat having an uncompressed L component 101 and compressed A and Bcomponents 105, 106.

Turning to FIG. 32, the pixels of for line n 110 are stored togetherbefore the pixels of for line and n+1 (111). With the image being storedin contiguous memory within a single channel.

In the 8 MB-memory model, the final Print Image after all processing isfinished, needs to be compressed in the chrominance channels.Compression of chrominance channels can be 4:1, causing an overallcompression of 12:6, or 2:1.

Other than the final Print Image, images in the Artcam are typically notcompressed. Because of memory constraints, software may choose tocompress the final Print Image in the chrominance channels by scalingeach of these channels by 2:1. If this has been done, the PRINT Varkfunction call utilised to print an image must be told to treat thespecified chrominance channels as compressed. The PRINT function is theonly function that knows how to deal with compressed chrominance, andeven so, it only deals with a fixed 2:1 compression ratio.

Although it is possible to compress an image and then operate on thecompressed image to create the final print image, it is not recommendeddue to a loss in resolution. In addition, an image should only becompressed once—as the final stage before printout. While onecompression is virtually undetectable, multiple compressions may causesubstantial image degradation.

Clip Image Organization

Clip images stored on Artcards have no explicit support by the ACP 31.Software is responsible for taking any images from the current Artcardand organizing the data into a form known by the ACP. If images arestored compressed on an Artcard, software is responsible fordecompressing them, as there is no specific hardware support fordecompression of Artcard images.

Image Pyramid Organization

During brushing, tiling, and warping processes utilised to manipulate animage it is often necessary to compute the average color of a particulararea in an image. Rather than calculate the value for each area given,these functions make use of an image pyramid. As illustrated in FIG. 33,an image pyramid is effectively a multi-resolution pixel-map. Theoriginal image 115 is a 1:1 representation. Low-pass filtering andsub-sampling by 2:1 in each dimension produces an image ¼ the originalsize 116. This process continues until the entire image is representedby a single pixel. An image pyramid is constructed from an originalinternal format image, and consumes ⅓ of the size taken up by theoriginal image (¼+ 1/16+ 1/64+ . . . ). For an original image of1500×1000 the corresponding image pyramid is approximately ½ MB. Animage pyramid is constructed by a specific Vark function, and is used asa parameter to other Vark functions.

Print Image Organization

The entire processed image is required at the same time in order toprint it. However the Print Image output can comprise a CMY ditheredimage and is only a transient image format, used within the Print Imagefunctionality. However, it should be noted that color conversion willneed to take place from the internal color space to the print colorspace. In addition, color conversion can be tuned to be different fordifferent print rolls in the camera with different ink characteristicse.g. Sepia output can be accomplished by using a specific sepia toningArtcard, or by using a sepia tone print-roll (so all Artcards will workin sepia tone).

Color Spaces

As noted previously there are 3 color spaces used in the Artcam,corresponding to the different image types.

The ACP has no direct knowledge of specific color spaces. Instead, itrelies on client color space conversion tables to convert between CCD,internal, and printer color spaces:

CCD: RGB

Internal: Lab

Printer: CMY

Removing the color space conversion from the ACP 31 allows:

-   -   Different CCDs to be used in different cameras    -   Different inks (in different print rolls over time) to be used        in the same camera    -   Separation of CCD selection from ACP design path    -   A well defined internal color space for accurate color        processing

Artcard Interface 87

The Artcard Interface (AI) takes data from the linear image Sensor whilean Artcard is passing under it, and makes that data available forstorage in DRAM. The image sensor produces 11,000 8-bit samples perscanline, sampling the Artcard at 4800 dpi. The AI is a state machinethat sends control information to the linear sensor, including LineSyncpulses and PixelClock pulses in order to read the image. Pixels are readfrom the linear sensor and placed into the VLIW Input FIFO 78. The VLIWis then able to process and/or store the pixels. The AI has only a fewregisters:

Description Register Name NumPixels The number of pixels in a sensorline (approx 11,000) Status The Print Head Interface's Status RegisterPixelsRemaining The number of bytes remaining in the current lineActions Reset A write to this register resets the AI, stops anyscanning, and loads all registers with 0. Scan A write to this registerwith a non-zero value sets the Scanning bit of the Status register, andcauses the Artcard Interface Scan cycle to start. A write to thisregister with 0 stops the scanning process and clears the Scanning bitin the Status register. The Scan cycle causes the AI to transferNumPixels bytes from the sensor to the VLIW Input FIFO 78, producing thePixelClock signals appropriately. Upon completion of NumPixels bytes, aLineSync pulse is given and the Scan cycle restarts. The PixelsRemainingregister holds the number of pixels remaining to be read on the currentscanline.

Note that the CPU should clear the VLIW Input FIFO 78 before initiatinga Scan. The Status register has bit interpretations as follows:

Bit Name Bits Description Scanning 1 If set, the AI is currentlyscanning, with the number of pixels remaining to be transferred from thecurrent line recorded in PixelsRemaining. If clear, the AI is notcurrently scanning, so is not transferring pixels to the VLIW Input FIFO78.

Artcard Interface (AI) 87

The Artcard Interface (AI) 87 is responsible for taking an Artcard imagefrom the Artcard Reader 34, and decoding it into the original data(usually a Vark script). Specifically, the AI 87 accepts signals fromthe Artcard scanner linear CCD 34, detects the bit pattern printed onthe card, and converts the bit pattern into the original data,correcting read errors.

With no Artcard 9 inserted, the image printed from an Artcam is simplythe sensed Photo Image cleaned up by any standard image processingroutines. The Artcard 9 is the means by which users are able to modify aphoto before printing it out. By the simple task of inserting a specificArtcard 9 into an Artcam, a user is able to define complex imageprocessing to be performed on the Photo Image.

With no Artcard inserted the Photo Image is processed in a standard wayto create the Print Image. When a single Artcard 9 is inserted into theArtcam, that Artcard's effect is applied to the Photo Image to generatethe Print Image.

When the Artcard 9 is removed (ejected), the printed image reverts tothe Photo Image processed in a standard way. When the user presses thebutton to eject an Artcard, an event is placed in the event queuemaintained by the operating system running on the Artcam CentralProcessor 31. When the event is processed (for example after the currentPrint has occurred), the following things occur:

If the current Artcard is valid, then the Print Image is marked asinvalid and a ‘Process Standard’ event is placed in the event queue.When the event is eventually processed it will perform the standardimage processing operations on the Photo Image to produce the PrintImage.

The motor is started to eject the Artcard and a time-specific‘Stop-Motor’ Event is added to the event queue.

Inserting an Artcard

When a user inserts an Artcard 9, the Artcard Sensor 49 detects itnotifying the ACP72. This results in the software inserting an ‘ArtcardInserted’ event into the event queue. When the event is processedseveral things occur:

The current Artcard is marked as invalid (as opposed to ‘none’).

The Print Image is marked as invalid.

The Artcard motor 37 is started up to load the Artcard

The Artcard Interface 87 is instructed to read the Artcard

The Artcard Interface 87 accepts signals from the Artcard scanner linearCCD 34, detects the bit pattern printed on the card, and corrects errorsin the detected bit pattern, producing a valid Artcard data block inDRAM.

Reading Data from the Artcard CCD—General Considerations

As illustrated in FIG. 34, the Data Card reading process has 4 phasesoperated while the pixel data is read from the card. The phases are asfollows:

Phase 1. Detect data area on Artcard

Phase 2. Detect bit pattern from Artcard based on CCD pixels, and writeas bytes.

Phase 3. Descramble and XOR the byte-pattern

Phase 4. Decode data (Reed-Solomon decode)

As illustrated in FIG. 35, the Artcard 9 must be sampled at least atdouble the printed resolution to satisfy Nyquist's Theorem. In practiceit is better to sample at a higher rate than this. Preferably, thepixels are sampled 230 at 3 times the resolution of a printed dot ineach dimension, requiring 9 pixels to define a single dot. Thus if theresolution of the Artcard 9 is 1600 dpi, and the resolution of thesensor 34 is 4800 dpi, then using a 50 mm CCD image sensor results in9450 pixels per column. Therefore if we require 2 MB of dot data (at 9pixels per dot) then this requires 2 MB*8*9/9450=15,978columns=approximately 16,000 columns. Of course if a dot is not exactlyaligned with the sampling CCD the worst and most likely case is that adot will be sensed over a 16 pixel area (4×4) 231.

An Artcard 9 may be slightly warped due to heat damage, slightly rotated(up to, say 1 degree) due to differences in insertion into an Artcardreader, and can have slight differences in true data rate due tofluctuations in the speed of the reader motor 37. These changes willcause columns of data from the card not to be read as correspondingcolumns of pixel data. As illustrated in FIG. 36, a 1 degree rotation inthe Artcard 9 can cause the pixels from a column on the card to be readas pixels across 166 columns:

Finally, the Artcard 9 should be read in a reasonable amount of timewith respect to the human operator. The data on the Artcard covers mostof the Artcard surface, so timing concerns can be limited to the Artcarddata itself. A reading time of 1.5 seconds is adequate for Artcardreading.

The Artcard should be loaded in 1.5 seconds. Therefore all 16,000columns of pixel data must be read from the CCD 34 in 1.5 second, i.e.10,667 columns per second. Therefore the time available to read onecolumn is 1/10667 seconds, or 93,747 ns. Pixel data can be written tothe DRAM one column at a time, completely independently from anyprocesses that are reading the pixel data.

The time to write one column of data (9450/2 bytes since the reading canbe 4 bits per pixel giving 2×4 bit pixels per byte) to DRAM is reducedby using 8 cache lines. If 4 lines were written out at one time, the 4banks can be written to independently, and thus overlap latency reduced.Thus the 4725 bytes can be written in 11,840 ns (4725/128*320 ns). Thusthe time taken to write a given column's data to DRAM uses just under13% of the available bandwidth.

Decoding an Artcard

A simple look at the data sizes shows the impossibility of fitting theprocess into the 8 MB of memory 33 if the entire Artcard pixel data (140MB if each bit is read as a 3×3 array) as read by the linear CCD 34 iskept. For this reason, the reading of the linear CCD, decoding of thebitmap, and the un-bitmap process should take place in real-time (whilethe Artcard 9 is traveling past the linear CCD 34), and these processesmust effectively work without having entire data stores available.

When an Artcard 9 is inserted, the old stored Print Image and anyexpanded Photo Image becomes invalid. The new Artcard 9 can containdirections for creating a new image based on the currently capturedPhoto Image. The old Print Image is invalid, and the area holdingexpanded Photo Image data and image pyramid is invalid, leaving morethan 5 MB that can be used as scratch memory during the read process.Strictly speaking, the 1 MB area where the Artcard raw data is to bewritten can also be used as scratch data during the Artcard read processas long as by the time the final Reed-Solomon decode is to occur, that 1MB area is free again. The reading process described here does not makeuse of the extra 1 MB area (except as a final destination for the data).

It should also be noted that the unscrambling process requires two setsof 2 MB areas of memory since unscrambling cannot occur in place.Fortunately the 5 MB scratch area contains enough space for thisprocess.

Turning now to FIG. 37, there is shown a flowchart 220 of the stepsnecessary to decode the Artcard data. These steps include reading in theArtcard 221, decoding the read data to produce corresponding encodedXORed scrambled bitmap data 223. Next a checkerboard XOR is applied tothe data to produces encoded scrambled data 224. This data is thenunscrambled 227 to produce data 225 before this data is subjected toReed-Solomon decoding to produce the original raw data 226.Alternatively, unscrambling and XOR process can take place together, notrequiring a separate pass of the data. Each of the above steps isdiscussed in further detail hereinafter. As noted previously withreference to FIG. 37, the Artcard Interface, therefore, has 4 phases,the first 2 of which are time-critical, and must take place while pixeldata is being read from the CCD:

Phase 1. Detect data area on Artcard

Phase 2. Detect bit pattern from Artcard based on CCD pixels, and writeas bytes.

Phase 3. Descramble and XOR the byte-pattern

Phase 4. Decode data (Reed-Solomon decode)

The four phases are described in more detail as follows:

Phase 1. As the Artcard 9 moves past the CCD 34 the AI must detect thestart of the data area by robustly detecting special targets on theArtcard to the left of the data area. If these cannot be detected, thecard is marked as invalid. The detection must occur in real-time, whilethe Artcard 9 is moving past the CCD 34.

If necessary, rotation invariance can be provided. In this case, thetargets are repeated on the right side of the Artcard, but relative tothe bottom right corner instead of the top corner. In this way thetargets end up in the correct orientation if the card is inserted the“wrong” way. Phase 3 below can be altered to detect the orientation ofthe data, and account for the potential rotation.

Phase 2. Once the data area has been determined, the main read processbegins, placing pixel data from the CCD into an ‘Artcard data window’,detecting bits from this window, assembling the detected bits intobytes, and constructing a byte-image in DRAM. This must all be donewhile the Artcard is moving past the CCD.

Phase 3. Once all the pixels have been read from the Artcard data area,the Artcard motor 37 can be stopped, and the byte image descrambled andXORed. Although not requiring real-time performance, the process shouldbe fast enough not to annoy the human operator. The process must take 2MB of scrambled bit-image and write the unscrambled/XORed bit-image to aseparate 2 MB image.

Phase 4. The final phase in the Artcard read process is the Reed-Solomondecoding process, where the 2 MB bit-image is decoded into a 1 MB validArtcard data area. Again, while not requiring real-time performance itis still necessary to decode quickly with regard to the human operator.If the decode process is valid, the card is marked as valid. If thedecode failed, any duplicates of data in the bit-image are attempted tobe decoded, a process that is repeated until success or until there areno more duplicate images of the data in the bit image.

The four phase process described requires 4.5 MB of DRAM. 2 MB isreserved for Phase 2 output, and 0.5 MB is reserved for scratch dataduring phases 1 and 2. The remaining 2 MB of space can hold over 440columns at 4725 byes per column. In practice, the pixel data being readis a few columns ahead of the phase 1 algorithm, and in the worst case,about 180 columns behind phase 2, comfortably inside the 440 columnlimit.

A description of the actual operation of each phase will now be providedin greater detail.

Phase 1—Detect Data Area on Artcard

This phase is concerned with robustly detecting the left-hand side ofthe data area on the Artcard 9. Accurate detection of the data area isachieved by accurate detection of special targets printed on the leftside of the card. These targets are especially designed to be easy todetect even if rotated up to 1 degree.

Turning to FIG. 38, there is shown an enlargement of the left hand sideof an Artcard 9. The side of the card is divided into 16 bands, 239 witha target e.g. 241 located at the center of each band. The bands arelogical in that there is no line drawn to separate bands. Turning toFIG. 39, there is shown a single target 241. The target 241, is aprinted black square containing a single white dot. The idea is todetect firstly as many targets 241 as possible, and then to join atleast 8 of the detected white-dot locations into a single logicalstraight line. If this can be done, the start of the data area 243 is afixed distance from this logical line. If it cannot be done, then thecard is rejected as invalid.

As shown in FIG. 38, the height of the card 9 is 3150 dots. A target(Target0) 241 is placed a fixed distance of 24 dots away from the topleft corner 244 of the data area so that it falls well within the firstof 16 equal sized regions 239 of 192 dots (576 pixels) with no target inthe final pixel region of the card. The target 241 must be big enough tobe easy to detect, yet be small enough not to go outside the height ofthe region if the card is rotated 1 degree. A suitable size for thetarget is a 31×31 dot (93×93 sensed pixels) black square 241 with thewhite dot 242.

At the worst rotation of 1 degree, a 1 column shift occurs every 57pixels. Therefore in a 590 pixel sized band, we cannot place any part ofour symbol in the top or bottom 12 pixels or so of the band or theycould be detected in the wrong band at CCD read time if the card isworst case rotated.

Therefore, if the black part of the rectangle is 57 pixels high (19dots) we can be sure that at least 9.5 black pixels will be read in thesame column by the CCD (worst case is half the pixels are in one columnand half in the next). To be sure of reading at least 10 black dots inthe same column, we must have a height of 20 dots. To give room forerroneous detection on the edge of the start of the black dots, weincrease the number of dots to 31, giving us 15 on either side of thewhite dot at the target's local coordinate (15, 15). 31 dots is 91pixels, which at most suffers a 3 pixel shift in column, easily withinthe 576 pixel band.

Thus each target is a block of 31×31 dots (93×93 pixels) each with thecomposition:

15 columns of 31 black dots each (45 pixel width columns of 93 pixels).

1 column of 15 black dots (45 pixels) followed by 1 white dot (3 pixels)and then a further 15 black dots (45 pixels)

15 columns of 31 black dots each (45 pixel width columns of 93 pixels)

Detect Targets

Targets are detected by reading columns of pixels, one column at a timerather than by detecting dots. It is necessary to look within a givenband for a number of columns consisting of large numbers of contiguousblack pixels to build up the left side of a target. Next, it is expectedto see a white region in the center of further black columns, andfinally the black columns to the left of the target center.

Eight cache lines are required for good cache performance on the readingof the pixels. Each logical read fills 4 cache lines via 4 sub-readswhile the other 4 cache-lines are being used. This effectively uses up13% of the available DRAM bandwidth.

As illustrated in FIG. 40, the detection mechanism FIFO for detectingthe targets uses a filter 245, run-length encoder 246, and a FIFO 247that requires special wiring of the top 3 elements (S1, S2, and S3) forrandom access.

The columns of input pixels are processed one at a time until either allthe targets are found, or until a specified number of columns have beenprocessed. To process a column, the pixels are read from DRAM, passedthrough a filter 245 to detect a 0 or 1, and then run length encoded246. The bit value and the number of contiguous bits of the same valueare placed in FIFO 247. Each entry of the FIFO 249 is in 8 bits, 7 bits250 to hold the run-length, and 1 bit 249 to hold the value of the bitdetected.

The run-length encoder 246 only encodes contiguous pixels within a 576pixel (192 dot) region.

The top 3 elements in the FIFO 247 can be accessed 252 in any randomorder. The run lengths (in pixels) of these entries are filtered into 3values: short, medium, and long in accordance with the following table:

Short Used to detect white dot. RunLength < 16 Medium Used to detectruns of black above or 16 <= RunLength < 48 below the white dot in thecenter of the target. Long Used to detect run lengths of black toRunLength >= 48 the left and right of the center dot in the target.Looking at the top three entries in the FIFO 247 there are 3 specificcases of interest:

Case 1 S1 = white long We have detected a black column of the S2 = blacklong target to the left of or to the right of S3 = white medium/ thewhite center dot. long Case 2 S1 = white long If we've been processing aseries of S2 = black medium columns of Case 1s, then we have S3 = whiteshort probably detected the white dot in this Previous 8 columns column.We know that the next entry will were Case 1 be black (or it would havebeen included in the white S3 entry), but the number of black pixels isin question. Need to verify by checking after the next FIFO advance (seeCase 3). Case 3 Prev = Case 2 We have detected part of the white dot. S3= black med We expect around 3 of these, and then some more columns ofCase 1.Preferably, the following information per region band is kept:

TargetDetected  1 bit BlackDetectCount  4 bits WhiteDetectCount  3 bitsPrevColumnStartPixel 15 bits TargetColumn ordinate 16 bits (15:1)TargetRow ordinate 16 bits (15:1) TOTAL 7 bytes (rounded to 8 bytes foreasy addressing)

Given a total of 7 bytes. It makes address generation easier if thetotal is assumed to be 8 bytes. Thus 16 entries requires 16*8=128 bytes,which fits in 4 cache lines. The address range should be inside thescratch 0.5 MB DRAM area since other phases make use of the remaining 4MB data area.

When beginning to process a given pixel column, the register valueS2StartPixel 254 is reset to 0. As entries in the FIFO advance from S2to Sl, they are also added 255 to the existing S2StartPixel value,giving the exact pixel position of the run currently defined in S2.Looking at each of the 3 cases of interest in the FIFO, S2StartPixel canbe used to determine the start of the black area of a target (Cases 1and 2), and also the start of the white dot in the center of the target(Case 3). An algorithm for processing columns can be as follows:

1 TargetDetected[0-15] := 0 BlackDetectCount[0-15] := 0WhiteDetectCount[0-15] := 0 TargetRow[0-15] := 0 TargetColumn[0-15] := 0PrevColStartPixel[0-15] := 0 CurrentColumn := 0 2 Do ProcessColumn 3CurrentColumn++ 4 If (CurrentColumn <= LastValidColumn) Goto 2The steps involved in the processing a column (Process Column) are asfollows:

1 S2StartPixel := 0 FIFO := 0 BlackDetectCount := 0 WhiteDetectCount :=0 ThisColumnDetected := FALSE PrevCaseWasCase2 := FALSE 2 If (!TargetDetected[Target]) & (! ColumnDetected[Target]) ProcessCases EndIf3 PrevCaseWasCase2 := Case=2 4 Advance FIFO

The processing for each of the 3 (Process Cases) cases is as follows:

Case 1:

BlackDetectCount[target] < 8 Δ := ABS(S2StartPixel − ORPrevColStartPixel[Target]) WhiteDetectCount[Target] = 0 If (0<=Δ< 2)BlackDetectCount[Target]++ (max value =8) Else BlackDetectCount[Target]:= 1 WhiteDetectCount[Target] := 0 EndIf PrevColStartPixel[Target] :=S2StartPixel ColumnDetected[Target] := TRUE BitDetected = 1BlackDetectCount[target] >= 8 PrevColStartPixel[Target] := S2StartPixelWhiteDetectCount[Target] != 0 ColumnDetected[Target] := TRUE BitDetected= 1 TargetDetected[Target] := TRUE TargetColumn[Target] := CurrentColumn− 8 − (WhiteDetectCount[Target]/2)

Case 2:

No special processing is recorded except for setting thePrevCaseWasCase2′ flag for identifying Case 3 (see Step 3 of processinga column described above)

Case 3:

PrevCaseWasCase2 = TRUE If (WhiteDetectCount[Target] < 2)BlackDetectCount[Target] >= 8 TargetRow[Target] = WhiteDetectCount=1S2StartPixel + (S2_(RunLength)/2) EndIf Δ := ABS(S2StartPixel −PrevColStartPixel[Target]) If (0<=Δ< 2) WhiteDetectCount[Target]++ ElseWhiteDetectCount[Target] := 1 EndIf PrevColStartPixel[Target] :=S2StartPixel ThisColumnDetected := TRUE BitDetected = 0

At the end of processing a given column, a comparison is made of thecurrent column to the maximum number of columns for target detection. Ifthe number of columns allowed has been HI exceeded, then it is necessaryto check how many targets have been found. If fewer than 8 have beenfound, the card is considered invalid.

Process Targets

After the targets have been detected, they should be processed. All thetargets may be available or merely some of them. Some targets may alsohave been erroneously detected.

This phase of processing is to determine a mathematical line that passesthrough the center of as many targets as possible. The more targets thatthe line passes through, the more confident the target position has beenfound. The limit is set to be 8 targets. If a line passes through atleast 8 targets, then it is taken to be the right one.

It is all right to take a brute-force but straightforward approach sincethere is the time to do so (see below), and lowering complexity makestesting easier. It is necessary to determine the line between targets 0and 1 (if both targets are considered valid) and then determine how manytargets fall on this line. Then we determine the line between targets 0and 2, and repeat the process. Eventually we do the same for the linebetween targets 1 and 2, 1 and 3 etc. and finally for the line betweentargets 14 and 15. Assuming all the targets have been found, we need toperform 15+14+13+ . . . =90 sets of calculations (with each set ofcalculations requiring 16 tests=1440 actual calculations), and choosethe line which has the maximum number of targets found along the line.The algorithm for target location can be as follows:

TargetA := 0 MaxFound := 0 BestLine := 0 While (TargetA < 15)   If(TargetA is Valid)   TargetB:= TargetA + 1   While (TargetB<= 15)   If(TargetB is valid)   CurrentLine := line between TargetA and TargetB  TargetC := 0;   While (TargetC <= 15)     If (TargetC valid ANDTargetC on line AB)       TargetsHit++     EndIf     If (TargetsHit >MaxFound)       MaxFound := TargetsHit       BestLine := CurrentLine    EndIf       TargetC++     EndWhile       EndIf   TargetB ++    EndWhile   EndIf   TargetA++ EndWhile If (MaxFound < 8)   Card isInvalid Else   Store expected centroids for rows based on BestLine EndIf

As illustrated in FIG. 34, in the algorithm above, to determine aCurrentLine 260 from Target A 261 and target B, it is necessary tocalculate Δrow (264) & Δcolumn (263) between targets 261, 262, and thelocation of Target A. It is then possible to move from Target 0 toTarget 1 etc. by adding Δrow and Δcolumn. The found (if actually found)location of target N can be compared to the calculated expected positionof Target N on the line, and if it falls within the tolerance, thenTarget N is determined to be on the line.

To calculate Δrow & Δcolumn:

Δrow=(row_(TargetA)−row_(TargetB))/(B−A)

Δcolumn=(column_(TargetA)−column_(TargetB))/(B−A)

Then we calculate the position of Target0:

row=rowTargetA−(A*Δrow)

column=columnTargetA−(A*Δcolumn)

And compare (row, column) against the actual row_(Target0) andcolumn_(Target0). To move from one expected target to the next (e.g.from Target0 to Target1), we simply add Δrow and Δcolumn to row andcolumn respectively. To check if each target is on the line, we mustcalculate the expected position of Target0, and then perform one add andone comparison for each target ordinate.

At the end of comparing all 16 targets against a maximum of 90 lines,the result is the best line through the valid targets. If that linepasses through at least 8 targets (i.e. MaxFound>=8), it can be saidthat enough targets have been found to form a line, and thus the cardcan be processed. If the best line passes through fewer than 8, then thecard is considered invalid.

The resulting algorithm takes 180 divides to calculate Δrow and Δcolumn,180 multiply/adds to calculate target0 position, and then 2880adds/comparisons. The time we have to perform this processing is thetime taken to read 36 columns of pixel data=3,374,892 ns. Not evenaccounting for the fact that an add takes less time than a divide, it isnecessary to perform 3240 mathematical operations in 3,374,892 ns. Thatgives approximately 1040 ns per operation, or 104 cycles. The CPU cantherefore safely perform the entire processing of targets, reducingcomplexity of design.

Update Centroids Based on Data Edge Border and Clockmarks

Step 0: Locate the Data Area

From Target 0 (241 of FIG. 38) it is a predetermined fixed distance inrows and columns to the top left border 244 of the data area, and then afurther 1 dot column to the vertical clock marks 276. So we use TargetA,Δrow and Δcolumn found in the previous stage (Δrow and Δcolumn refer todistances between targets) to calculate the centroid or expectedlocation for Target0 as described previously.

Since the fixed pixel offset from Target0 to the data area is related tothe distance between targets (192 dots between targets, and 24 dotsbetween Target0 and the data area 243), simply add Δrow/8 to Target0'scentroid column coordinate (aspect ratio of dots is 1:1). Thus the topco-ordinate can be defined as:

(column_(DotColumnTop)=column_(Target0)+(Δrow/8)

(row_(DotColumnTop)=row_(Target)0+(Δcolumn/8)

Next Δrow and Δcolumn are updated to give the number of pixels betweendots in a single column (instead of between targets) by dividing them bythe number of dots between targets:

Δrow=Δrow/192

Δcolumn=Δcolumn/192

We also set the currentColumn register (see Phase 2) to be −1 so thatafter step 2, when phase 2 begins, the currentColumn register willincrement from −1 to 0.

Step 1: Write Out the Initial Centroid Deltas (Δ) and Bit History

This simply involves writing setup information required for Phase 2.

This can be achieved by writing 0s to all the Δrow and Δcolumn entriesfor each row, and a bit history. The bit history is actually an expectedbit history since it is known that to the left of the clock mark column276 is a border column 277, and before that, a white area. The bithistory therefore is 011, 010, 011, 010 etc.

Step 2: Update the Centroids Based on Actual Pixels Read.

The bit history is set up in Step 1 according to the expected clockmarks and data border. The actual centroids for each dot row can now bemore accurately set (they were initially 0) by comparing the expecteddata against the actual pixel values. The centroid updating mechanism isachieved by simply performing step 3 of Phase 2.

Phase 2—Detect Bit Pattern from Artcard Based on Pixels Read, and Writeas Bytes.

Since a dot from the Artcard 9 requires a minimum of 9 sensed pixelsover 3 columns to be represented, there is little point in performingdot detection calculations every sensed pixel column. It is better toaverage the time required for processing over the average dotoccurrence, and thus make the most of the available processing time.This allows processing of a column of dots from an Artcard 9 in the timeit takes to read 3 columns of data from the Artcard. Although the mostlikely case is that it takes 4 columns to represent a dot, the 4^(th)column will be the last column of one dot and the first column of a nextdot. Processing should therefore be limited to only 3 columns.

As the pixels from the CCD are written to the DRAM in 13% of the timeavailable, 83% of the time is available for processing of 1 column ofdots i.e. 83% of (93,747*3)=83% of 281,241 ns=233,430 ns.

In the available time, it is necessary to detect 3150 dots, and writetheir bit values into the raw data area of memory. The processingtherefore requires the following steps:

For each column of dots on the Artcard:

Step 0: Advance to the next dot column

Step 1: Detect the top and bottom of an Artcard dot column (check clockmarks)

Step 2: Process the dot column, detecting bits and storing themappropriately

Step 3: Update the centroids

Since we are processing the Artcard's logical dot columns, and these mayshift over 165 pixels, the worst case is that we cannot process thefirst column until at least 165 columns have been read into DRAM. Phase2 would therefore finish the same amount of time after the read processhad terminated. The worst case time is: 165*93,747 ns=15,468,255 ns or0.015 seconds.

Step 0: Advance to the Next Dot Column

In order to advance to the next column of dots we add Δrow and Δcolumnto the dotColumnTop to give us the centroid of the dot at the top of thecolumn. The first time we do this, we are currently at the clock markscolumn 276 to the left of the bit image data area, and so we advance tothe first column of data. Since Δrow and Δcolumn refer to distancebetween dots within a column, to move between dot columns it isnecessary to add Δrow to column_(dotColumnTop) and Δcolumn torow_(dotColumnTop).

To keep track of what column number is being processed, the columnnumber is recorded in a register called CurrentColumn. Every time thesensor advances to the next dot column it is necessary to increment theCurrentColumn register. The first time it is incremented, it isincremented from −1 to 0 (see Step 0 Phase 1). The CurrentColumnregister determines when to terminate the read process (when reachingmaxColumns), and also is used to advance the DataOut Pointer to the nextcolumn of byte information once all 8 bits have been written to the byte(once every 8 dot columns). The lower 3 bits determine what bit we're upto within the current byte. It will be the same bit being written forthe whole column.

Step 1: Detect the Top and Bottom of an Artcard Dot Column.

In order to process a dot column from an Artcard, it is necessary todetect the top and bottom of a column. The column should form a straightline between the top and bottom of the column (except for local warpingetc.). Initially dotColumnTop points to the clock mark column 276. Wesimply toggle the expected value, write it out into the bit history, andmove on to step 2, whose first task will be to add the Δrow and Δcolumnvalues to dotColumnTop to arrive at the first data dot of the column.

Step 2: Process an Artcard's Dot Column

Given the centroids of the top and bottom of a column in pixelcoordinates the column should form a straight line between them, withpossible minor variances due to warping etc.

Assuming the processing is to start at the top of a column (at the topcentroid coordinate) and move down to the bottom of the column,subsequent expected dot centroids are given as:

row_(next)=row+Δrow

column_(next)=column+Δcolumn

This gives us the address of the expected centroid for the next dot ofthe column. However to account for local warping and error we addanother Δrow and Δcolumn based on the last time we found the dot in agiven row. In this way we can account for small drifts that accumulateinto a maximum drift of some percentage from the straight line joiningthe top of the column to the bottom.

We therefore keep 2 values for each row, but store them in separatetables since the row history is used in step 3 of this phase.

-   -   Δrow and Δcolumn (2 @ 4 bits each=1 byte)    -   row history (3 bits per row, 2 rows are stored per byte)

For each row we need to read a Δrow and Δcolumn to determine the changeto the centroid. The read process takes 5% of the bandwidth and 2 cachelines:

76*(3150/32)+2*3150=13,824 ns=5% of bandwidth

Once the centroid has been determined, the pixels around the centroidneed to be examined to detect the status of the dot and hence the valueof the bit. In the worst case a dot covers a 4×4 pixel area. However,thanks to the fact that we are sampling at 3 times the resolution of thedot, the number of pixels required to detect the status of the dot andhence the bit value is much less than this. We only require access to 3columns of pixel columns at any one time.

In the worst case of pixel drift due to a 1% rotation, centroids willshift 1 column every 57 pixel rows, but since a dot is 3 pixels indiameter, a given column will be valid for 171 pixel rows (3*57). As abyte contains 2 pixels, the number of bytes valid in each buffered read(4 cache lines) will be a worst case of 86 (out of 128 read).

Once the bit has been detected it must be written out to DRAM. We storethe bits from 8 columns as a set of contiguous bytes to minimize DRAMdelay. Since all the bits from a given dot column will correspond to thenext bit position in a data byte, we can read the old value for thebyte, shift and OR in the new bit, and write the byte back. Theread/shift&OR/write process requires 2 cache lines.

We need to read and write the bit history for the given row as we updateit. We only require 3 bits of history per row, allowing the storage of 2rows of history in a single byte. The read/shift&OR/write processrequires 2 cache lines.

The total bandwidth required for the bit detection and storage issummarised in the following table:

Read centroid Δ  5% Read 3 columns of pixel data 19% Read/Write detectedbits into byte buffer 10% Read/Write bit history  5% TOTAL 39%

Detecting a Dot

The process of detecting the value of a dot (and hence the value of abit) given a centroid is accomplished by examining 3 pixel values andgetting the result from a lookup table. The process is fairly simple andis illustrated in FIG. 42. A dot 290 has a radius of about 1.5 pixels.Therefore the pixel 291 that holds the centroid, regardless of theactual position of the centroid within that pixel, should be 100% of thedot's value. If the centroid is exactly in the center of the pixel 291,then the pixels above 292 & below 293 the centroid's pixel, as well asthe pixels to the left 294 & right 295 of the centroid's pixel willcontain a majority of the dot's value. The further a centroid is awayfrom the exact center of the pixel 295, the more likely that more thanthe center pixel will have 100% coverage by the dot.

Although FIG. 42 only shows centroids differing to the left and belowthe center, the same relationship obviously holds for centroids aboveand to the right of center. center. In Case 1, the centroid is exactlyin the center of the middle pixel 295. The center pixel 295 iscompletely covered by the dot, and the pixels above, below, left, andright are also well covered by the dot. In Case 2, the centroid is tothe left of the center of the middle pixel 291. The center pixel isstill completely covered by the dot, and the pixel 294 to the left ofthe center is now completely covered by the dot. The pixels above 292and below 293 are still well covered. In Case 3, the centroid is belowthe center of the middle pixel 291. The center pixel 291 is stillcompletely covered by the dot 291, and the pixel below center is nowcompletely covered by the dot. The pixels left 294 and right 295 ofcenter are still well covered. In Case 4, the centroid is left and belowthe center of the middle pixel. The center pixel 291 is still completelycovered by the dot, and both the pixel to the left of center 294 and thepixel below center 293 are completely covered by the dot.

The algorithm for updating the centroid uses the distance of thecentroid from the center of the middle pixel 291 in order to select 3representative pixels and thus decide the value of the dot:

Pixel 1: the pixel containing the centroid

Pixel 2: the pixel to the left of Pixel 1 if the centroid's X coordinate(column value) is <½, otherwise the pixel to the right of Pixel 1.

Pixel 3: the pixel above pixel 1 if the centroid's Y coordinate (rowvalue) is <½, otherwise the pixel below Pixel 1.

As shown in FIG. 43, the value of each pixel is output to apre-calculated lookup table 301. The 3 pixels are fed into a 12-bitlookup table, which outputs a single bit indicating the value of thedot—on or off. The lookup table 301 is constructed at chip definitiontime, and can be compiled into about 500 gates. The lookup table can bea simple threshold table, with the exception that the center pixel(Pixel 1) is weighted more heavily.

Step 3: Update the Centroid Δs for Each Row in the Column

The idea of the Δs processing is to use the previous bit history togenerate a ‘perfect’ dot at the expected centroid location for each rowin a current column. The actual pixels (from the CCD) are compared withthe expected ‘perfect’ pixels. If the two match, then the actualcentroid location must be exactly in the expected position, so thecentroid Δs must be valid and not need updating. Otherwise a process ofchanging the centroid Δs needs to occur in order to best fit theexpected centroid location to the actual data. The new centroid Δs willbe used for processing the dot in the next column.

Updating the centroid Δs is done as a subsequent process from Step 2 forthe following reasons:

to reduce complexity in design, so that it can be performed as Step 2 ofPhase 1 there is enough bandwidth remaining to allow it to allow reuseof DRAM buffers, and

to ensure that all the data required for centroid updating is availableat the start of the process without special pipelining.

The centroid Δ are processed as Δcolumn Δrow respectively to reducecomplexity.

Although a given dot is 3 pixels in diameter, it is likely to occur in a4×4 pixel area. However the edge of one dot will as a result be in thesame pixel as the edge of the next dot. For this reason, centroidupdating requires more than simply the information about a given singledot.

FIG. 44 shows a single dot 310 from the previous column with a givencentroid 311. In this example, the dot 310 extend Δ over 4 pixel columns312-315 and in fact, part of the previous dot column's dot(coordinate=(Prevcolumn, Current Row)) has entered the current columnfor the dot on the current row. If the dot in the current row and columnwas white, we would expect the rightmost pixel column 314 from theprevious dot column to be a low value, since there is only the dotinformation from the previous column's dot (the current column's dot iswhite). From this we can see that the higher the pixel value is in thispixel column 315, the more the centroid should be to the right Ofcourse, if the dot to the right was also black, we cannot adjust thecentroid as we cannot get information sub-pixel. The same can be saidfor the dots to the left, above and below the dot at dot coordinates(PrevColumn, CurrentRow).

From this we can say that a maximum of 5 pixel columns and rows arerequired. It is possible to simplify the situation by taking the casesof row and column centroid Δs separately, treating them as the sameproblem, only rotated 90 degrees.

Taking the horizontal case first, it is necessary to change the columncentroid Δs if the expected pixels don't match the detected pixels. Fromthe bit history, the value of the bits found for the Current Row in thecurrent dot column, the previous dot column, and the (previous−1)th dotcolumn are known. The expected centroid location is also known. Usingthese two pieces of information, it is possible to generate a 20 bitexpected bit pattern should the read be ‘perfect’. The 20 bitbit-pattern represents the expected Δ values for each of the 5 pixelsacross the horizontal dimension. The first nibble would represent therightmost pixel of the leftmost dot. The next 3 nibbles represent the 3pixels across the center of the dot 310 from the previous column, andthe last nibble would be the leftmost pixel 317 of the rightmost dot(from the current column).

If the expected centroid is in the center of the pixel, we would expecta 20 bit pattern based on the following table:

Bit history Expected pixels 000 00000 001 0000D 010 0DFD0 011 0DFDD 100D0000 101 D000D 110 DDFD0 111 DDFDD

The pixels to the left and right of the center dot are either 0 or Ddepending on whether the bit was a 0 or 1 respectively. The center threepixels are either 000 or DFD depending on whether the bit was a 0 or 1respectively. These values are based on the physical area taken by a dotfor a given pixel. Depending on the distance of the centroid from theexact center of the pixel, we would expect data shifted slightly, whichreally only affects the pixels either side of the center pixel. Sincethere are 16 possibilities, it is possible to divide the distance fromthe center by 16 and use that amount to shift the expected pixels.

Once the 20 bit 5 pixel expected value has been determined it can becompared against the actual pixels read. This can proceed by subtractingthe expected pixels from the actual pixels read on a pixel by pixelbasis, and finally adding the differences together to obtain a distancefrom the expected Δ values.

FIG. 45 illustrates one form of implementation of the above algorithmwhich includes a look up table 320 which receives the bit history 322and central fractional component 323 and outputs 324 the corresponding20 bit number which is subtracted 321 from the central pixel input 326to produce a pixel difference 327.

This process is carried out for the expected centroid and once for ashift of the centroid left and right by 1 amount in Δcolumn. Thecentroid with the smallest difference from the actual pixels isconsidered to be the ‘winner’ and the Δcolumn updated accordingly (whichhopefully is ‘no change’). As a result, a Δcolumn cannot change by morethan 1 each dot column.

The process is repeated for the vertical pixels, and Δrow isconsequentially updated.

There is a large amount of scope here for parallelism. Depending on therate of the clock chosen for the ACP unit 31 these units can be placedin series (and thus the testing of 3 different Δ could occur inconsecutive clock cycles), or in parallel where all 3 can be testedsimultaneously. If the clock rate is fast enough, there is less need forparallelism.

Bandwidth Utilization

It is necessary to read the old Δ of the Δs, and to write them outagain. This takes 10% of the bandwidth:

2*(76(3150/32)+2*3150)=27,648 ns=10% of bandwidth

It is necessary to read the bit history for the given row as we updateits Δs. Each byte contains 2 row's bit histories, thus taking 2.5% ofthe bandwidth:

76((3150/2)/32)+2*(3150/2)=4,085 ns=2.5% of bandwidth

In the worst case of pixel drift due to a 1% rotation, centroids willshift 1 column every 57 pixel rows, but since a dot is 3 pixels indiameter, a given pixel column will be valid for 171 pixel rows (3*57).As a byte contains 2 pixels, the number of bytes valid in cached readswill be a worst case of 86 (out of 128 read). The worst case timing for5 columns is therefore 31% bandwidth.

5*(((9450/(128*2))*320)*128/86)=88, 112 ns=31% of bandwidth.

The total bandwidth required for the updating the centroid Δ issummarised in the following table:

Read/Write centroid Δ 10% Read bit history 2.5%  Read 5 columns of pixeldata 31% TOTAL 43.5% 

Memory Usage for Phase 2:

The 2 MB bit-image DRAM area is read from and written to during Phase 2processing. The 2 MB pixel-data DRAM area is read.

The 0.5 MB scratch DRAM area is used for storing row data, namely:

Centroid array 24 bits (16:8) * 2 * 3150 = 18,900 byes Bit History array3 bits * 3150 entries (2 per byte) = 1575 bytes

Phase 3—Unscramble and XOR the Raw Data

Returning to FIG. 37, the next step in decoding is to unscramble and XORthe raw data. The 2 MB byte image, as taken from the Artcard, is in ascrambled XORed form. It must be unscrambled and re-XORed to retrievethe bit image necessary for the Reed Solomon decoder in phase 4.

Turning to FIG. 46, the unscrambling process 330 takes a 2 MB scrambledbyte image 331 and writes an unscrambled 2 MB image 332. The processcannot reasonably be performed in-place, so 2 sets of 2 MB areas areutilised. The scrambled data 331 is in symbol block order arranged in a16×16 array, with symbol block 0 (334) having all the symbol 0's fromall the code words in random order. Symbol block 1 has all the symbol1's from all the code words in random order etc. Since there are only255 symbols, the 256^(th) symbol block is currently unused.

A linear feedback shift register is used to determine the relationshipbetween the position within a symbol block e.g. 334 and what code worde.g. 355 it came from. This works as long as the same seed is used whengenerating the original Artcard images. The XOR of bytes fromalternative source lines with 0xAA and 0x55 respectively is effectivelyfree (in time) since the bottleneck of time is waiting for the DRAM tobe ready to read/write to non-sequential addresses.

The timing of the unscrambling XOR process is effectively 2 MB of randombyte-reads, and 2 MB of random byte-writes i.e. 2*(2 MB*76 ns+2 MB*2ns)=327,155,712 ns or approximately 0.33 seconds. This timing assumes nocaching.

Phase 4—Reed Solomon Decode

This phase is a loop, iterating through copies of the data in the bitimage, passing them to the Reed-Solomon decode module until either asuccessful decode is made or until there are no more copies to attemptdecode from.

The Reed-Solomon decoder used can be the VLIW processor, suitablyprogrammed or, alternatively, a separate hardwired core such as LSILogic's L64712. The L64712 has a throughput of 50 Mbits per second(around 6.25 MB per second), so the time may be bound by the speed ofthe Reed-Solomon decoder rather than the 2 MB read and 1 MB write memoryaccess time (500 MB/sec for sequential accesses). The time taken in theworst case is thus 2/6.25 s=approximately 0.32 seconds.

Phase 5 Running the Vark Script

The overall time taken to read the Artcard 9 and decode it is thereforeapproximately 2.15 seconds. The apparent delay to the user is actuallyonly 0.65 seconds (the total of Phases 3 and 4), since the Artcard stopsmoving after 1.5 seconds.

Once the Artcard is loaded, the Artvark script must be interpreted,Rather than run the script immediately, the script is only run upon thepressing of the ‘Print’ button 13 (FIG. 1). The taken to run the scriptwill vary depending on the complexity of the script, and must be takeninto account for the perceived delay between pressing the print buttonand the actual print button and the actual printing.

Alternative Artcard Format

Of course, other artcard formats are possible. There will now bedescribed one such alternative artcard format with a number ofpreferable feature. Described hereinafter will be the alternativeArtcard data format, a mechanism for mapping user data onto dots on analternative Artcard, and a fast alternative Artcard reading algorithmfor use in embedded systems where resources are scarce.

Alternative Artcard Overview

The Alternative Artcards can be used in both embedded and PC typeapplications, providing a user-friendly interface to large amounts ofdata or configuration information.

While the back side of an alternative Artcard has the same visualappearance regardless of the application (since it stores the data), thefront of an alternative Artcard can be application dependent. It mustmake sense to the user in the context of the application.

Alternative Artcard technology can also be independent of the printingresolution. The notion of storing data as dots on a card simply meansthat if it is possible put more dots in the same space (by increasingresolution), then those dots can represent more data. The preferredembodiment assumes utilisation of 1600 dpi printing on a 86 mm×55 mmcard as the sample Artcard, but it is simple to determine alternativeequivalent layouts and data sizes for other card sizes and/or otherprint resolutions. Regardless of the print resolution, the readingtechnique remain the same. After all decoding and other overhead hasbeen taken into account, alternative Artcards are capable of storing upto 1 Megabyte of data at print resolutions up to 1600 dpi. AlternativeArtcards can store megabytes of data at print resolutions greater than1600 dpi. The following two tables summarize the effective alternativeArtcard data storage capacity for certain print resolutions:

Format of an Alternative Artcard

The structure of data on the alternative Artcard is thereforespecifically designed to aid the recovery of data. This sectiondescribes the format of the data (back) side of an alternative Artcard.

Dots

The dots on the data side of an alternative Artcard can be monochrome.For example, black dots printed on a white background at a predetermineddesired print resolution. Consequently a “black dot” is physicallydifferent from a “white dot”. FIG. 47 illustrates various examples ofmagnified views of black and white dots. The monochromatic scheme ofblack dots on a white background is preferably chosen to maximizedynamic range in blurry reading environments. Although the black dotsare printed at a particular pitch (e.g. 1600 dpi), the dots themselvesare slightly larger in order to create continuous lines when dots areprinted contiguously. In the example images of FIG. 47, the dots are notas merged as they may be in reality as a result of bleeding. There wouldbe more smoothing out of the black indentations. Although thealternative Artcard system described in the preferred embodiment allowsfor flexibly different dot sizes, exact dot sizes and ink/printingbehaviour for a particular printing technology should be studied in moredetail in order to obtain best results.

In describing this artcard embodiment, the term dot refers to a physicalprinted dot (ink, thermal, electro-photographic, silver-halide etc) onan alternative Artcard. When an alternative Artcard reader scans analternative Artcard, the dots must be sampled at least double theprinted resolution to satisfy Nyquist's Theorem. The term pixel refersto a sample value from an alternative Artcard reader device. Forexample, when 1600 dpi dots are scanned at 4800 dpi there are 3 pixelsin each dimension of a dot, or 9 pixels per dot. The sampling processwill be further explained hereinafter.

Turning to FIG. 48, there is shown the data surface 1101 a sample ofalternative Artcard. Each alternative Artcard consists of an “active”region 1102 surrounded by a white border region 1103. The white border1103 contains no data information, but can be used by an alternativeArtcard reader to calibrate white levels. The active region is an arrayof data blocks e.g. 1104, with each data block separated from the nextby a gap of 8 white dots e.g. 1106. Depending on the print resolution,the number of data blocks on an alternative Artcard will vary. On a 1600dpi alternative Artcard, the array can be 8×8. Each data block 1104 hasdimensions of 627×394 dots. With an inter-block gap 1106 of 8 whitedots, the active area of an alternative Artcard is therefore 5072×3208dots (8.1 mm×5.1 mm at 1600 dpi).

Data Blocks

Turning now to FIG. 49, there is shown a single data block 1107. Theactive region of an alternative Artcard consists of an array ofidentically structured data blocks 1107. Each of the data blocks has thefollowing structure: a data region 1108 surrounded by clock-marks 1109,borders 1110, and targets 1111. The data region holds the encoded dataproper, while the clock-marks, borders and targets are presentspecifically to help locate the data region and ensure accurate recoveryof data from within the region.

Each data block 1107 has dimensions of 627×394 dots. Of this, thecentral area of 595×384 dots is the data region 1108. The surroundingdots are used to hold the clock-marks, borders, and targets.

Borders and Clockmarks

FIG. 50 illustrates a data block with FIG. 51 and FIG. 52 illustratingmagnified edge portions thereof. As illustrated in FIG. 51 and FIG. 52,there are two 5 dot high border and clockmark regions 1170, 1177 in eachdata block: one above and one below the data region. For example, Thetop 5 dot high region consists of an outer black dot border line 1112(which stretches the length of the data block), a white dot separatorline 1113 (to ensure the border line is independent), and a 3 dot highset of clock marks 1114. The clock marks alternate between a white andblack row, starting with a black clock mark at the 8th column fromeither end of the data block. There is no separation between clockmarkdots and dots in the data region.

The clock marks are symmetric in that if the alternative Artcard isinserted rotated 180 degrees, the same relative border/clockmark regionswill be encountered. The border 1112, 1113 is intended for use by analternative Artcard reader to keep vertical tracking as data is readfrom the data region. The clockmarks 1114 are intended to keephorizontal tracking as data is read from the data region. The separationbetween the border and clockmarks by a white line of dots is desirableas a result of blurring occurring during reading. The border thusbecomes a black line with white on either side, making for a goodfrequency response on reading. The clockmarks alternating between whiteand black have a similar result, except in the horizontal rather thanthe vertical dimension. Any alternative Artcard reader must locate theclockmarks and border if it intends to use them for tracking. The nextsection deals with targets, which are designed to point the way to theclockmarks, border and data.

Targets in the Target Region

As shown in FIG. 54, there are two 15-dot wide target regions 1116, 1117in each data block: one to the left and one to the right of the dataregion. The target regions are separated from the data region by asingle column of dots used for orientation. The purpose of the TargetRegions 1116, 1117 is to point the way to the clockmarks, border anddata regions. Each Target Region contains 6 targets e.g. 1118 that aredesigned to be easy to find by an alternative Artcard reader. Turningnow to FIG. 53 there is shown the structure of a single target 1120.Each target 1120 is a 15×15 dot black square with a center structure1121 and a run-length encoded target number 1122. The center structure1121 is a simple white cross, and the target number component 1122 issimply two columns of white dots, each being 2 dots long for each partof the target number. Thus target number 1's target id 1122 is 2 dotslong, target number 2's target id 1122 is 4 dots wide etc.

As shown in FIG. 54, the targets are arranged so that they are rotationinvariant with regards to card insertion. This means that the lefttargets and right targets are the same, except rotated 180 degrees. Inthe left Target Region 1116, the targets are arranged such that targets1 to 6 are located top to bottom respectively. In the right TargetRegion, the targets are arranged so that target numbers 1 to 6 arelocated bottom to top. The target number id is always in the halfclosest to the data region. The magnified view portions of FIG. 54reveals clearly the how the right targets are simply the same as theleft targets, except rotated 180 degrees.

As shown in FIG. 55, the targets 1124, 1125 are specifically placedwithin the Target Region with centers 55 dots apart. In addition, thereis a distance of 55 dots from the center of target 1 (1124) to the firstclockmark dot 1126 in the upper clockmark region, and a distance of 55dots from the center of the target to the first clockmark dot in thelower clockmark region (not shown). The first black clockmark in bothregions begins directly in line with the target center (the 8th dotposition is the center of the 15 dot-wide target).

The simplified schematic illustrations of FIG. 55 illustrates thedistances between target centers as well as the distance from Target 1(1124) to the first dot of the first black clockmark (1126) in the upperborder/clockmark region. Since there is a distance of 55 dots to theclockmarks from both the upper and lower targets, and both sides of thealternative Artcard are symmetrical (rotated through 180 degrees), thecard can be read left-to-right or right-to-left. Regardless of readingdirection, the orientation does need to be determined in order toextract the data from the data region.

Orientation Columns

As illustrated in FIG. 56, there are two 1 dot wide Orientation Columns1127, 1128 in each data block: one directly to the left and one directlyto the right of the data region. The Orientation Columns are present togive orientation information to an alternative Artcard reader: On theleft side of the data region (to the right of the Left Targets) is asingle column of white dots 1127. On the right side of the data region(to the left of the Right Targets) is a single column of black dots1128. Since the targets are rotation invariant, these two columns ofdots allow an alternative Artcard reader to determine the orientation ofthe alternative Artcard—has the card been inserted the right way, orback to front.

From the alternative Artcard reader's point of view, assuming nodegradation to the dots, there are two possibilities:

-   -   If the column of dots to the left of the data region is white,        and the column to the right of the data region is black, then        the reader will know that the card has been inserted the same        way as it was written.    -   If the column of dots to the left of the data region is black,        and the column to the right of the data region is white, then        the reader will know that the card has been inserted backwards,        and the data region is appropriately rotated. The reader must        take appropriate action to correctly recover the information        from the alternative Artcard.

Data Region

As shown in FIG. 57, the data region of a data block consists of 595columns of 384 dots each, for a total of 228,480 dots. These dots mustbe interpreted and decoded to yield the original data. Each dotrepresents a single bit, so the 228,480 dots represent 228,480 bits, or28,560 bytes. The interpretation of each dot can be as follows:

Black 1 White 0

The actual interpretation of the bits derived from the dots, however,requires understanding of the mapping from the original data to the dotsin the data regions of the alternative Artcard.

Mapping Original Data to Data Region Dots

There will now be described the process of taking an original data fileof maximum size 910,082 bytes and mapping it to the dots in the dataregions of the 64 data blocks on a 1600 dpi alternative Artcard. Analternative Artcard reader would reverse the process in order to extractthe original data from the dots on an alternative Artcard. At firstglance it seems trivial to map data onto dots: binary data is comprisedof 1s and 0s, so it would be possible to simply write black and whitedots onto the card. This scheme however, does not allow for the factthat ink can fade, parts of a card may be damaged with dirt, grime, oreven scratches. Without error-detection encoding, there is no way todetect if the data retrieved from the card is correct. And withoutredundancy encoding, there is no way to correct the detected errors. Theaim of the mapping process then, is to make the data recovery highlyrobust, and also give the alternative Artcard reader the ability to knowit read the data correctly.

There are three basic steps involved in mapping an original data file todata region dots:

-   -   Redundancy encode the original data    -   Shuffle the encoded data in a deterministic way to reduce the        effect of localized alternative Artcard damage    -   Write out the shuffled, encoded data as dots to the data blocks        on the alternative Artcard

Each of these steps is examined in detail in the following sections.

Redundancy Encode Using Reed-Solomon Encoding

The mapping of data to alternative Artcard dots relies heavily on themethod of redundancy encoding employed. Reed-Solomon encoding ispreferably chosen for its ability to deal with burst errors andeffectively detect and correct errors using a minimum of redundancy.Reed Solomon encoding is adequately discussed in the standard texts suchas Wicker, S., and Bhargava, V., 1994, Reed-Solomon Codes and theirApplications, IEEE Press. Rorabaugh, C, 1996, Error Coding Cookbook,McGraw-Hill. Lyppens, H., 1997, Reed-Solomon Error Correction, Dr.Dobb's Journal, January 1997 (Volume 22, Issue 1).

A variety of different parameters for Reed-Solomon encoding can be used,including different symbol sizes and different levels of redundancy.Preferably, the following encoding parameters are used:

-   -   m=8    -   t=64

Having m=8 means that the symbol size is 8 bits (1 byte). It also meansthat each Reed-Solomon encoded block size n is 255 bytes (2⁸−1 symbols).In order to allow correction of up to t symbols, 2t symbols in the finalblock size must be taken up with redundancy symbols. Having t=64 meansthat 64 bytes (symbols) can be corrected per block if they are in error.Each 255 byte block therefore has 128 (2×64) redundancy bytes, and theremaining 127 bytes (k=127) are used to hold original data. Thus:

-   -   n=255    -   k=127

The practical result is that 127 bytes of original data are encoded tobecome a 255-byte block of Reed-Solomon encoded data. The encoded255-byte blocks are stored on the alternative Artcard and later decodedback to the original 127 bytes again by the alternative Artcard reader.The 384 dots in a single column of a data block's data region can hold48 bytes (384/8). 595 of these columns can hold 28,560 bytes. Thisamounts to 112 Reed-Solomon blocks (each block having 255 bytes). The 64data blocks of a complete alternative Artcard can hold a total of 7168Reed-Solomon blocks (1,827,840 bytes, at 255 bytes per Reed-Solomonblock). Two of the 7,168 Reed-Solomon blocks are reserved for controlinformation, but the remaining 7166 are used to store data. Since eachReed-Solomon block holds 127 bytes of actual data, the total amount ofdata that can be stored on an alternative Artcard is 910,082 bytes(7166×127). If the original data is less than this amount, the data canbe encoded to fit an exact number of Reed-Solomon blocks, and then theencoded blocks can be replicated until all 7,166 are used. FIG. 58illustrates the overall form of encoding utilised.

Each of the 2 Control blocks 1132, 1133 contain the same encodedinformation required for decoding the remaining 7,166 Reed-Solomonblocks:

The number of Reed-Solomon blocks in a full message (16 bits storedlo/hi), and

The number of data bytes in the last Reed-Solomon block of the message(8 bits)

These two numbers are repeated 32 times (consuming. 96 bytes) with theremaining 31 bytes reserved and set to 0. Each control block is thenReed-Solomon encoded, turning the 127 bytes of control information into255 bytes of Reed-Solomon encoded data.

The Control Block is stored twice to give greater chance of itsurviving. In addition, the repetition of the data within the ControlBlock has particular significance when using Reed-Solomon encoding. Inan uncorrupted Reed-Solomon encoded block, the first 127 bytes of dataare exactly the original data, and can be looked at in an attempt torecover the original message if the Control Block fails decoding (morethan 64 symbols are corrupted). Thus, if a Control Block fails decoding,it is possible to examine sets of 3 bytes in an effort to determine themost likely values for the 2 decoding parameters. It is not guaranteedto be recoverable, but it has a better chance through redundancy. Saythe last 159 bytes of the Control Block are destroyed, and the first 96bytes are perfectly ok. Looking at the first 96 bytes will show arepeating set of numbers. These numbers can be sensibly used to decodethe remainder of the message in the remaining 7,166 Reed-Solomon blocks.

By way of example, assume a data file containing exactly 9,967 bytes ofdata. The number of Reed-Solomon blocks required is 79. The first 78Reed-Solomon blocks are completely utilized, consuming 9,906 bytes(78×127). The 79th block has only 61 bytes of data (with the remaining66 bytes all 0s).

The alternative Artcard would consist of 7,168 Reed-Solomon blocks. Thefirst 2 blocks would be Control Blocks, the next 79 would be the encodeddata, the next 79 would be a duplicate of the encoded data, the next 79would be another duplicate of the encoded data, and so on. After storingthe 79 Reed-Solomon blocks 90 times, the remaining 56 Reed-Solomonblocks would be another duplicate of the first 56 blocks from the 79blocks of encoded data (the final 23 blocks of encoded data would not bestored again as there is not enough room on the alternative Artcard). Ahex representation of the 127 bytes in each Control Block data beforebeing Reed-Solomon encoded would be as illustrated in FIG. 59.

Scramble the Encoded Data

Assuming all the encoded blocks have been stored contiguously in memory,a maximum 1,827,840 bytes of data can be stored on the alternativeArtcard (2 Control Blocks and 7,166 information blocks, totalling 7,168Reed-Solomon encoded blocks). Preferably, the data is not directlystored onto the alternative Artcard at this stage however, or all 255bytes of one Reed-Solomon block will be physically together on the card.Any dirt, grime, or stain that causes physical damage to the card hasthe potential of damaging more than 64 bytes in a single Reed-Solomonblock, which would make that block unrecoverable. If there are noduplicates of that Reed-Solomon block, then the entire alternativeArtcard cannot be decoded.

The solution is to take advantage of the fact that there are a largenumber of bytes on the alternative Artcard, and that the alternativeArtcard has a reasonable physical size. The data can therefore bescrambled to ensure that symbols from a single Reed-Solomon block arenot in close proximity to one another. Of course pathological cases ofcard degradation can cause Reed-Solomon blocks to be unrecoverable, buton average, the scrambling of data makes the card much more robust. Thescrambling scheme chosen is simple and is illustrated schematically inFIG. 14. All the Byte 0s from each Reed-Solomon block are placedtogether 1136, then all the Byte is etc. There will therefore be 7,168byte 0's, then 7,168 Byte 1's etc. Each data block on the alternativeArtcard can store 28,560 bytes. Consequently there are approximately 4bytes from each Reed-Solomon block in each of the 64 data blocks on thealternative Artcard.

Under this scrambling scheme, complete damage to 16 entire data blockson the alternative Artcard will result in 64 symbol errors perReed-Solomon block. This means that if there is no other damage to thealternative Artcard, the entire data is completely recoverable, even ifthere is no data duplication.

Write the Scrambled Encoded Data to the Alternative Artcard

Once the original data has been Reed-Solomon encoded, duplicated, andscrambled, there are 1,827,840 bytes of data to be stored on thealternative Artcard. Each of the 64 data blocks on the alternativeArtcard stores 28,560 bytes.

The data is simply written out to the alternative Artcard data blocks sothat the first data block contains the first 28,560 bytes of thescrambled data, the second data block contains the next 28,560 bytesetc.

As illustrated in FIG. 61, within a data block, the data is written outcolumn-wise left to right. Thus the left-most column within a data blockcontains the first 48 bytes of the 28,560 bytes of scrambled data, andthe last column contains the last 48 bytes of the 28,560 bytes ofscrambled data. Within a column, bytes are written out top to bottom,one bit at a time, starting from bit 7 and finishing with bit 0. If thebit is set (1), a black dot is placed on the alternative Artcard, if thebit is clear (0), no dot is placed, leaving it the white backgroundcolor of the card.

For example, a set of 1,827,840 bytes of data can be created byscrambling 7,168 Reed-Solomon encoded blocks to be stored onto analternative Artcard. The first 28,560 bytes of data are written to thefirst data block. The first 48 bytes of the first 28,560 bytes arewritten to the first column of the data block, the next 48 bytes to thenext column and so on. Suppose the first two bytes of the 28,560 bytesare hex D3 5F. Those first two bytes will be stored in column 0 of thedata block. Bit 7 of byte 0 will be stored first, then bit 6 and so on.Then Bit 7 of byte 1 will be stored through to bit 0 of byte 1. Sinceeach “1” is stored as a black dot, and each “0” as a white dot, thesetwo bytes will be represented on the alternative Artcard as thefollowing set of dots:

-   -   D3 (1101 0011) becomes: black, black, white, black, white,        white, black, black    -   5F (0101 1111) becomes: white, black, white, black, black,        black, black, black

Decoding an Alternative Artcard

This section deals with extracting the original data from an alternativeArtcard in an accurate and robust manner. Specifically, it assumes thealternative Artcard format as described in the previous chapter, anddescribes a method of extracting the original pre-encoded data from thealternative Artcard.

There are a number of general considerations that are part of theassumptions for decoding an alternative Artcard.

User

The purpose of an alternative Artcard is to store data for use indifferent applications. A user inserts an alternative Artcard into analternative Artcard reader, and expects the data to be loaded in a“reasonable time”. From the user's perspective, a motor transport movesthe alternative Artcard into an alternative Artcard reader. This is notperceived as a problematic delay, since the alternative Artcard is inmotion. Any time after the alternative Artcard has stopped is perceivedas a delay, and should be minimized in any alternative Artcard readingscheme. Ideally, the entire alternative Artcard would be read while inmotion, and thus there would be no perceived delay after the card hadstopped moving.

For the purpose of the preferred embodiment, a reasonable time for analternative Artcard to be physically loaded is defined to be 1.5seconds. There should be a minimization of time for additional decodingafter the alternative Artcard has stopped moving. Since the Activeregion of an alternative Artcard covers most of the alternative Artcardsurface we can limit our timing concerns to that region.

Sampling Dots

The dots on an alternative Artcard must be sampled by a CCD reader orthe like at least at double the printed resolution to satisfy Nyquist'sTheorem. In practice it is better to sample at a higher rate than this.In the alternative Artcard reader environment, dots are preferablysampled at 3 times their printed resolution in each dimension, requiring9 pixels to define a single dot. If the resolution of the alternativeArtcard dots is 1600 dpi, the alternative Artcard reader's image sensormust scan pixels at 4800 dpi. Of course if a dot is not exactly alignedwith the sampling sensor, the worst and most likely case as illustratedin FIG. 62, is that a dot will be sensed over a 4×4 pixel area.

Each sampled pixel is 1 byte (8 bits). The lowest 2 bits of each pixelcan contain significant noise. Decoding algorithms must therefore benoise tolerant.

Alignment/Rotation

It is extremely unlikely that a user will insert an alternative Artcardinto an alternative Artcard reader perfectly aligned with no rotation.Certain physical constraints at a reader entrance and motor transportgrips will help ensure that once inserted, an alternative Artcard willstay at the original angle of insertion relative to the CCD. Preferablythis angle of rotation, as illustrated in FIG. 63 is a maximum of 1degree. There can be some slight aberrations in angle due to jitter andmotor rumble during the reading process, but these are assumed toessentially stay within the 1-degree limit.

The physical dimensions of an alternative Artcard are 86 mm×55 mm. A 1degree rotation adds 1.5 mm to the effective height of the card as 86 mmpasses under the CCD (86 sin 1°), which will affect the required CCDlength.

The effect of a 1 degree rotation on alternative Artcard reading is thata single scanline from the CCD will include a number of differentcolumns of dots from the alternative Artcard. This is illustrated in anexaggerated form in FIG. 63 which shows the drift of dots across thecolumns of pixels. Although exaggerated in this diagram, the actualdrift will be a maximum 1 pixel column shift every 57 pixels.

When an alternative Artcard is not rotated, a single column of dots canbe read over 3 pixel scanlines. The more an alternative Artcard isrotated, the greater the local effect. The more dots being read, thelonger the rotation effect is applied. As either of these factorsincrease, the larger the number of pixel scanlines that are needed to beread to yield a given set of dots from a single column on an alternativeArtcard. The following table shows how many pixel scanlines are requiredfor a single column of dots in a particular alternative Artcardstructure.

Region Height 0° rotation 1° rotation Active region 3208 dots 3 pixelcolumns 168 pixel columns Data block  394 dots 3 pixel columns  21 pixelcolumns

To read an entire alternative Artcard, we need to read 87 mm (86 mm+1 mmdue to 1° rotation). At 4800 dpi this implies 16,252 pixel columns.

CCD (or Other Linear Image Sensor) Length

The length of the CCD itself must accommodate:

-   -   the physical height of the alternative Artcard (55 mm),    -   vertical slop on physical alternative Artcard insertion (1 mm)    -   insertion rotation of up to 1 degree (86 sin 1°=1.5 mm)

These factors combine to form a total length of 57.5 mm.

When the alternative Artcard Image sensor CCD in an alternative Artcardreader scans at 4800 dpi, a single scanline is 10,866 pixels. Forsimplicity, this figure has been rounded up to 11,000 pixels. The ActiveRegion of an alternative Artcard has a height of 3208 dots, whichimplies 9,624 pixels. A Data Region has a height of 384 dots, whichimplies 1,152 pixels.

DRAM Size

The amount of memory required for alternative Artcard reading anddecoding is ideally minimized. The typical placement of an alternativeArtcard reader is an embedded system where memory resources areprecious. This is made more problematic by the effects of rotation. Asdescribed above, the more an alternative Artcard is rotated, the morescanlines are required to effectively recover original dots.

There is a trade-off between algorithmic complexity, user perceiveddelays, robustness, and memory usage. One of the simplest readeralgorithms would be to simply scan the whole alternative Artcard, andthen to process the whole data without real-time constraints. Not onlywould this require huge reserves of memory, it would take longer than areader algorithm that occurred concurrently with the alternative Artcardreading process.

The actual amount of memory required for reading and decoding analternative Artcard is twice the amount of space required to hold theencoded data, together with a small amount of scratch space (1-2 KB).For the 1600 dpi alternative Artcard, this implies a 4 MB memoryrequirement. The actual usage of the memory is detailed in the followingalgorithm description.

Transfer Rate

DRAM bandwidth assumptions need to be made for timing considerations andto a certain extent affect algorithmic design, especially sincealternative Artcard readers are typically part of an embedded system.

A standard Rambus Direct RDRAM architecture is assumed, as defined inRambus Inc, October 1997, Direct Rambus Technology Disclosure, with apeak data transfer rate of 1.6 GB/sec. Assuming 75% efficiency (easilyachieved), we have an average of 1.2 GB/sec data transfer rate. Theaverage time to access a block of 16 bytes is therefore 12 ns.

Dirty Data

Physically damaged alternative Artcards can be inserted into a reader.Alternative Artcards may be scratched, or be stained with grime or dirt.A alternative Artcard reader can't assume to read everything perfectly.The effect of dirty data is made worse by blurring, as the dirty dataaffects the surrounding clean dots.

Blurry Environment

There are two ways that blurring is introduced into the alternativeArtcard reading environment:

-   -   Natural blurring due to nature of the CCD's distance from the        alternative Artcard.    -   Warping of alternative Artcard

Natural blurring of an alternative Artcard image occurs when there isoverlap of sensed data from the CCD. Blurring can be useful, as theoverlap ensures there are no high frequencies in the sensed data, andthat there is no data missed by the CCD. However if the area covered bya CCD pixel is too large, there will be too much blurring and thesampling required to recover the data will not be met. FIG. 64 is aschematic illustration of the overlapping of sensed data.

Another form of blurring occurs when an alternative Artcard is slightlywarped due to heat damage. When the warping is in the verticaldimension, the distance between the alternative Artcard and the CCD willnot be constant, and the level of blurring will vary across those areas.

Black and white dots were chosen for alternative Artcards to give thebest dynamic range in blurry reading environments. Blurring can causeproblems in attempting to determine whether a given dot is black orwhite.

As the blurring increases, the more a given dot is influenced by thesurrounding dots. Consequently the dynamic range for a particular dotdecreases. Consider a white dot and a black dot, each surrounded by allpossible sets of dots. The 9 dots are blurred, and the center dotsampled. FIG. 65 shows the distribution of resultant center dot valuesfor black and white dots.

The diagram is intended to be a representative blurring. The curve 1140from 0 to around 180 shows the range of black dots. The curve 1141 from75 to 250 shows the range of white dots. However the greater theblurring, the more the two curves shift towards the center of the rangeand therefore the greater the intersection area, which means the moredifficult it is to determine whether a given dot is black or white. Apixel value at the center point of intersection is ambiguous—the dot isequally likely to be a black or a white.

As the blurring increases, the likelihood of a read bit error increases.Fortunately, the Reed-Solomon decoding algorithm can cope with thesegracefully up to t symbol errors. FIG. 65 is a graph of number predictednumber of alternative Artcard Reed-Solomon blocks that cannot berecovered given a particular symbol error rate. Notice how theReed-Solomon decoding scheme performs well and then substantiallydegrades. If there is no Reed-Solomon block duplication, then only 1block needs to be in error for the data to be unrecoverable. Of course,with block duplication the chance of an alternative Artcard decodingincreases.

FIG. 66 only illustrates the symbol (byte) errors corresponding to thenumber of Reed-Solomon blocks in error. There is a trade-off between theamount of blurring that can be coped with, compared to the amount ofdamage that has been done to a card. Since all error detection andcorrection is performed by a Reed-Solomon decoder, there is a finitenumber of errors per Reed-Solomon data block that can be coped with. Themore errors introduced through blurring, the fewer the number of errorsthat can be coped with due to alternative Artcard damage.

Overview of Alternative Artcard Decoding

As noted previously, when the user inserts an alternative Artcard intoan alternative Artcard reading unit, a motor transport ideally carriesthe alternative Artcard past a monochrome linear CCD image sensor. Thecard is sampled in each dimension at three times the printed resolution.Alternative Artcard reading hardware and software compensate forrotation up to 1 degree, jitter and vibration due to the motortransport, and blurring due to variations in alternative Artcard to CCDdistance. A digital bit image of the data is extracted from the sampledimage by a complex method described here. Reed-Solomon decoding correctsarbitrarily distributed data corruption of up to 25% of the raw data onthe alternative Artcard. Approximately 1 MB of corrected data isextracted from a 1600 dpi card.

The steps involved in decoding are so as indicated in FIG. 67.

The decoding process requires the following steps:

-   -   Scan 1144 the alternative Artcard at three times printed        resolution (eg scan 1600 dpi alternative Artcard at 4800 dpi)    -   Extract 1145 the data bitmap from the scanned dots on the card.    -   Reverse 1146 the bitmap if the alternative Artcard was inserted        backwards.    -   Unscramble 1147 the encoded data    -   Reed-Solomon 1148 decode the data from the bitmap

Algorithmic Overview Phase 1—Real Time Bit Image Extraction

A simple comparison between the available memory (4 MB) and the memoryrequired to hold all the scanned pixels for a 1600 dpi alternativeArtcard (172.5 MB) shows that unless the card is read multiple times(not a realistic option), the extraction of the bitmap from the pixeldata must be done on the fly, in real time, while the alternativeArtcard is moving past the CCD. Two tasks must be accomplished in thisphase:

-   -   Scan the alternative Artcard at 4800 dpi    -   Extract the data bitmap from the scanned dots on the card

The rotation and unscrambling of the bit image cannot occur until thewhole bit image has been extracted. It is therefore necessary to assigna memory region to hold the extracted bit image. The bit image fitseasily within 2 MB, leaving 2 MB for use in the extraction process.

Rather than extracting the bit image while looking only at the currentscanline of pixels from the CCD, it is possible to allocate a buffer toact as a window onto the alternative Artcard, storing the last Nscanlines read. Memory requirements do not allow the entire alternativeArtcard to be stored this way (172.5 MB would be required), butallocating 2 MB to store 190 pixel columns (each scanline takes lessthan 11,000 bytes) makes the bit image extraction process simpler.

The 4 MB memory is therefore used as follows:

-   -   2 MB for the extracted bit image    -   ˜2 MB for the scanned pixels    -   1.5 KB for Phase 1 scratch data (as required by algorithm)

The time taken for Phase 1 is 1.5 seconds, since this is the time takenfor the alternative Artcard to travel past the CCD and physically load.

Phase 2—Data Extraction from Bit Image

Once the bit image has been extracted, it must be unscrambled andpotentially rotated 180°. It must then be decoded. Phase 2 has noreal-time requirements, in that the alternative Artcard has stoppedmoving, and we are only concerned with the user's perception of elapsedtime. Phase 2 therefore involves the remaining tasks of decoding analternative Artcard:

-   -   Re-organize the bit image, reversing it if the alternative        Artcard was inserted backwards    -   Unscramble the encoded data    -   Reed-Solomon decode the data from the bit image

The input to Phase 2 is the 2 MB bit image buffer. Unscrambling androtating cannot be performed in situ, so a second 2 MB buffer isrequired. The 2 MB buffer used to hold scanned pixels in Phase 1 is nolonger required and can be used to store the rotated unscrambled data.

The Reed-Solomon decoding task takes the unscrambled bit image anddecodes it to 910,082 bytes. The decoding can be performed in situ, orto a specified location elsewhere. The decoding process does not requireany additional memory buffers.

The 4 MB memory is therefore used as follows:

-   -   2 MB for the extracted bit image (from Phase 1)    -   ˜2 MB for the unscrambled, potentially rotated bit image    -   <1 KB for Phase 2 scratch data (as required by algorithm)

The time taken for Phase 2 is hardware dependent and is bound by thetime taken for Reed-Solomon decoding. Using a dedicated core such as LSILogic's L64712, or an equivalent CPU/DSP combination, it is estimatedthat Phase 2 would take 0.32 seconds.

Phase 1—Extract Bit Image

This is the real-time phase of the algorithm, and is concerned withextracting the bit image from the alternative Artcard as scanned by theCCD.

As shown in FIG. 68 Phase 1 can be divided into 2 asynchronous processstreams. The first of these streams is simply the real-time reader ofalternative Artcard pixels from the CCD, writing the pixels to DRAM. Thesecond stream involves looking at the pixels, and extracting the bits.The second process stream is itself divided into 2 processes. The firstprocess is a global process, concerned with locating the start of thealternative Artcard. The second process is the bit image extractionproper.

FIG. 69 illustrates the data flow from a data/process perspective.

Timing

For an entire 1600 dpi alternative Artcard, it is necessary to read amaximum of 16,252 pixel-columns. Given a total time of 1.5 seconds forthe whole alternative Artcard, this implies a maximum time of 92,296 nsper pixel column during the course of the various processes.

Process 1—Read Pixels from CCD

The CCD scans the alternative Artcard at 4800 dpi, and generates 11,0001-byte pixel samples per column. This process simply takes the data fromthe CCD and writes it to DRAM, completely independently of any otherprocess that is reading the pixel data from DRAM. FIG. 70 illustratesthe steps involved.

The pixels are written contiguously to a 2 MB buffer that can hold 190full columns of pixels. The buffer always holds the 190 columns mostrecently read. Consequently, any process that wants to read the pixeldata (such as Processes 2 and 3) must firstly know where to look for agiven column, and secondly, be fast enough to ensure that the datarequired is actually in the buffer.

Process 1 makes the current scanline number (CurrentScanLine) availableto other processes so they can ensure they are not attempting to accesspixels from scanlines that have not been read yet.

The time taken to write out a single column of data (11,000 bytes) toDRAM is:

11,000/16*12=8,256 ns

Process 1 therefore uses just under 9% of the available DRAM bandwidth(8256/92296).

Process 2—Detect Start of Alternative Artcard

This process is concerned with locating the Active Area on a scannedalternative Artcard. The input to this stage is the pixel data from DRAM(placed there by Process 1). The output is a set of bounds for the first8 data blocks on the alternative Artcard, required as input to Process3. A high level overview of the process can be seen in FIG. 71.

An alternative Artcard can have vertical slop of 1 mm upon insertion.With a rotation of 1 degree there is further vertical slop of 1.5 mm (86sin 1°). Consequently there is a total vertical slop of 2.5 mm. At 1600dpi, this equates to a slop of approximately 160 dots. Since a singledata block is only 394 dots high, the slop is just under half a datablock. To get a better estimate of where the data blocks are located thealternative Artcard itself needs to be detected.

Process 2 therefore consists of two parts:

-   -   Locate the start of the alternative Artcard, and if found,    -   Calculate the bounds of the first 8 data blocks based on the        start of the alternative Artcard.

Locate the Start of the Alternative Artcard

The scanned pixels outside the alternative Artcard area are black (thesurface can be black plastic or some other non-reflective surface). Theborder of the alternative Artcard area is white. If we process the pixelcolumns one by one, and filter the pixels to either black or white, thetransition point from black to white will mark the start of thealternative Artcard. The highest level process is as follows:

for (Column=0; Column < MAX_COLUMN; Column++) {   Pixel =ProcessColumn(Column)   if (Pixel)       return (Pixel, Column)   //success! } return failure           // no alternative Artcard found

The ProcessColumn function is simple. Pixels from two areas of thescanned column are passed through a threshold filter to determine ifthey are black or white. It is possible to then wait for a certainnumber of white pixels and announce the start of the alternative Artcardonce the given number has been detected. The logic of processing a pixelcolumn is shown in the following pseudocode. 0 is returned if thealternative Artcard has not been detected during the column. Otherwisethe pixel number of the detected location is returned.

// Try upper region first count = 0 for (i=0; i<UPPER_REGION_BOUND; i++){ if (GetPixel(column, i) < THRESHOLD) {         count = 0    // pixelis black   }   else   { count++ // pixel is white if (count >WHITE_ALTERNATIVE ARTCARD)             return i   } } // Try lowerregion next. Process pixels in reverse count = 0 for (i=MAX_PIXEL_BOUND;i>LOWER_REGION_BOUND; i−−) { if (GetPixel(column, i) < THRESHOLD) {count = 0 // pixel is black } else { count++ // pixel is white if(count > WHITE_ALTERNATIVE ARTCARD)             return i   } } //Not inupper bound or in lower bound. Return failure return 0

Calculate Data Block Bounds

At this stage, the alternative Artcard has been detected. Depending onthe rotation of the alternative Artcard, either the top of thealternative Artcard has been detected or the lower part of thealternative Artcard has been detected. The second step of Process 2determines which was detected and sets the data block bounds for Phase 3appropriately.

A look at Phase 3 reveals that it works on data block segment bounds:each data block has a StartPixel and an EndPixel to determine where tolook for targets in order to locate the data block's data region.

If the pixel value is in the upper half of the card, it is possible tosimply use that as the first StartPixel bounds. If the pixel value is inthe lower half of the card, it is possible to move back so that thepixel value is the last segment's EndPixel bounds. We step forwards orbackwards by the alternative Artcard data size, and thus set up eachsegment with appropriate bounds. We are now ready to begin extractingdata from the alternative Artcard.

// Adjust to become first pixel if is lower pixel if (pixel >LOWER_REGION_BOUND) { pixel −= 6 * 1152 if (pixel < 0)          pixel =0 } for (i=0; i<6; i++) { endPixel = pixel + 1152 segment[i].MaxPixel =MAX_PIXEL_BOUND segment[i].SetBounds(pixel, endPixel) pixel = endPixel }

The MaxPixel value is defined in Process 3, and the SetBounds functionsimply sets StartPixel and EndPixel clipping with respect to 0 andMaxPixel.

Process 3—Extract Bit Data from Pixels

This is the heart of the alternative Artcard Reader algorithm. Thisprocess is concerned with extracting the bit data from the CCD pixeldata. The process essentially creates a bit-image from the pixel data,based on scratch information created by Process 2, and maintained byProcess 3. A high level overview of the process can be seen in FIG. 72.

Rather than simply read an alternative Artcard's pixel column anddetermine what pixels belong to what data block, Process 3 works theother way around. It knows where to look for the pixels of a given datablock. It does this by dividing a logical alternative Artcard into 8segments, each containing 8 data blocks as shown in FIG. 73.

The segments as shown match the logical alternative Artcard. Physically,the alternative Artcard is likely to be rotated by some amount. Thesegments remain locked to the logical alternative Artcard structure, andhence are rotation-independent. A given segment can have one of twostates:

-   -   LookingForTargets: where the exact data block position for this        segment has not yet been determined. Targets are being located        by scanning pixel column data in the bounds indicated by the        segment bounds. Once the data block has been located via the        targets, and bounds set for black & white, the state changes to        ExtractingBitImage.    -   ExtractingBitlmage: where the data block has been accurately        located, and bit data is being extracted one dot column at a        time and written to the alternative Artcard bit image. The        following of data block clockmarks gives accurate dot recovery        regardless of rotation, and thus the segment bounds are ignored.        Once the entire data block has been extracted, new segment        bounds are calculated for the next data block based on the        current position. The state changes to LookingForTargets.

The process is complete when all 64 data blocks have been extracted, 8from each region.

Each data block consists of 595 columns of data, each with 48 bytes.Preferably, the 2 orientation columns for the data block are eachextracted at 48 bytes each, giving a total of 28,656 bytes extracted perdata block. For simplicity, it is possible to divide the 2 MB of memoryinto 64×32 k chunks. The nth data block for a given segment is stored atthe location:

StartBuffer+(256 k*n)

Data Structure for Segments

Each of the 8 segments has an associated data structure. The datastructure defining each segment is stored in the scratch data area. Thestructure can be as set out in the following table:

DataName Comment CurrentState Defines the current state of the segment.Can be one of: LookingForTargets ExtractingBitImage Initial value isLookingForTargets Used during LookingForTargets: StartPixel Upper pixelbound of segment. Initially set by Process 2. EndPixel Lower pixel boundof segment. Initially set by Process 2 MaxPixel The maximum pixel numberfor any scanline. It is set to the same value for each segment: 10,866.CurrentColumn Pixel column we're up to while looking for targets.FinalColumn Defines the last pixel column to look in for targets.LocatedTargets Points to a list of located Targets. PossibleTargetsPoints to a set of pointers to Target structures that representcurrently investigated pixel shapes that may be targets AvailableTargetsPoints to a set of pointers to Target structures that are currentlyunused. TargetsFound The number of Targets found so far in this datablock. PossibleTargetCount The number of elements in the PossibleTargetslist AvailabletargetCount The number of elements in the AvailableTargetslist Used during ExtractingBitImage: BitImage The start of the Bit Imagedata area in DRAM where to store the next data block: Segment 1 = X,Segment 2 = X + 32k etc Advances by 256k each time the state changesfrom ExtractingBitImageData to Looking ForTargets CurrentByte Offsetwithin BitImage where to store next extracted byte CurrentDotColumnHolds current clockmark/dot column number. Set to −8 when transitioningfrom state LookingForTarget to ExtractingBitImage. UpperClock Coordinate(column/pixel) of current upper clockmark/border LowerClock Coordinate(column/pixel) of current lower clockmark/border CurrentDot The centerof the current data dot for the current dot column. Initially set to thecenter of the first (topmost) dot of the data column. DataDelta What toadd (column/pixel) to CurrentDot to advance to the center of the nextdot. BlackMax Pixel value above which a dot is definitely white WhiteMinPixel value below which a dot is definitely black MidRange The pixelvalue that has equal likelihood of coming from black or white. When allsmarts have not determined the dot, this value is used to determine it.Pixels below this value are black, and above it are white.

High Level of Process 3

Process 3 simply iterates through each of the segments, performing asingle line of processing depending on the segment's current state. Thepseudocode is straightforward:

blockCount = 0 while (blockCount < 64)   for (i=0; i<8; i++)   {  finishedBlock = segment[i].ProcessState( )   if (finishedBlock)           blockCount++ }

Process 3 must be halted by an external controlling process if it hasnot terminated after a specified amount of time. This will only be thecase if the data cannot be extracted. A simple mechanism is to start acountdown after Process 1 has finished reading the alternative Artcard.If Process 3 has not finished by that time, the data from thealternative Artcard cannot be recovered.

CurrentState=LookingForTargets

Targets are detected by reading columns of pixels, one pixel-column at atime rather than by detecting dots within a given band of pixels(between StartPixel and EndPixel) certain patterns of pixels aredetected. The pixel columns are processed one at a time until either allthe targets are found, or until a specified number of columns have beenprocessed. At that time the targets can be processed and the data arealocated via clockmarks. The state is changed to ExtractingBitImage tosignify that the data is now to be extracted. If enough valid targetsare not located, then the data block is ignored, skipping to a columndefinitely within the missed data block, and then beginning again theprocess of looking for the targets in the next data block. This can beseen in the following pseudocode:

finishedBlock = FALSE if(CurrentColumn < Process1.CurrentScanLine) {ProcessPixelColumn( ) CurrentColumn++ } if ((TargetsFound == 6) ||(CurrentColumn > LastColumn)) { if (TargetsFound >= 2)         ProcessTargets( )    if (TargetsFound >= 2)    {BuildClockmarkEstimates( ) SetBlackAndWhiteBounds( ) CurrentState =ExtractingBitImage CurrentDotColumn = −8    }    else    { // data blockcannot be recovered. Look for // next instead. Must adjust pixel boundsto // take account of possible 1 degree rotation. finishedBlock = TRUESetBounds(StartPixel−12, EndPixel+12) BitImage += 256KB CurrentByte = 0LastColumn += 1024 TargetsFound = 0    } } return finishedBlock

ProcessPixelColumn

Each pixel column is processed within the specified bounds (betweenStartPixel and EndPixel) to search for certain patterns of pixels whichwill identify the targets. The structure of a single target (targetnumber 2) is as previously shown in FIG. 54:

From a pixel point of view, a target can be identified by:

-   -   Left black region, which is a number of pixel columns consisting        of large numbers of contiguous black pixels to build up the        first part of the target.    -   Target center, which is a white region in the center of further        black columns    -   Second black region, which is the 2 black dot columns after the        target center    -   Target number, which is a black-surrounded white region that        defines the target number by its length    -   Third black region, which is the 2 black columns after the        target number

An overview of the required process is as shown in FIG. 74.

Since identification only relies on black or white pixels, the pixels1150 from each column are passed through a filter 1151 to detect blackor white, and then run length encoded 1152. The run-lengths are thenpassed to a state machine 1153 that has access to the last 3 run lengthsand the 4th last color. Based on these values, possible targets passthrough each of the identification stages.

The GatherMin&Max process 1155 simply keeps the minimum & maximum pixelvalues encountered during the processing of the segment. These are usedonce the targets have been located to set BlackMax, WhiteMin, andMidRange values.

Each segment keeps a set of target structures in its search for targets.While the target structures themselves don't move around in memory,several segment variables point to lists of pointers to these targetstructures. The three pointer lists are repeated here:

LocatedTargets Points to a set of Target structures that representlocated targets. PossibleTargets Points to a set of pointers to Targetstructures that represent currently investigated pixel shapes that maybe targets. AvailableTargets Points to a set of pointers to Targetstructures that are currently unused.

There are counters associated with each of these list pointers:TargetsFound, PossibleTargetCount, and AvailableTargetCountrespectively.

Before the alternative Artcard is loaded, TargetsFound andPossibleTargetCount are set to 0, and AvailableTargetCount is set to 28(the maximum number of target structures possible to have underinvestigation since the minimum size of a target border is 40 pixels,and the data area is approximately 1152 pixels). An example of thetarget pointer layout is as illustrated in FIG. 75.

As potential new targets are found, they are taken from theAvailableTargets list 1157, the target data structure is updated, andthe pointer to the structure is added to the PossibleTargets list 1158.When a target is completely verified, it is added to the LocatedTargetslist 1159. If a possible target is found not to be a target after all,it is placed back onto the AvailableTargets list 1157. Consequentlythere are always 28 target pointers in circulation at any time, movingbetween the lists.

The Target data structure 1160 can have the following form:

DataName Comment CurrentState The current state of the target searchDetectCount Counts how long a target has been in a given stateStartPixel Where does the target start? All the lines of pixels in thistarget should start within a tolerance of this pixel value. TargetNumberWhich target number is this (according to what was read) Column Bestestimate of the target's center column ordinate Pixel Best estimate ofthe target's center pixel ordinate

The ProcessPixelColumn function within the find targets module 1162(FIG. 74) then, goes through all the run lengths one by one, comparingthe runs against existing possible targets (via StartPixel), or creatingnew possible targets if a potential target is found where none waspreviously known. In all cases, the comparison is only made if S0.coloris white and S1.color is black.

The pseudocode for the ProcessPixelColumn set out hereinafter. When thefirst target is positively identified, the last column to be checked fortargets can be determined as being within a maximum distance from it.For 1° rotation, the maximum distance is 18 pixel columns.

pixel = StartPixel t = 0 target=PossibleTarget[t] while ((pixel <EndPixel) && (TargetsFound < 6)) {   if ((S0.Color == white) &&(S1.Color == black))   {      do      {       keepTrying = FALSE      if       (         (target != NULL)         &&        (target->AddToTarget(Column, pixel, S1, S2, S3))       )       {        if (target->CurrentState == IsATarget)         {          Removetarget from PossibleTargets List          Add target to LocatedTargetsList          TargetsFound++          if (TargetsFound == 1)           FinalColumn = Column +            MAX_TARGET_DELTA}         }        else if (target->CurrentState == NotATarget)         {         Remove target from PossibleTargets List          Add target toAvailableTargets List          keepTrying = TRUE         }         else        {          t++  // advance to next target         }        target = PossibleTarget[t]       }       else       {        tmp = AvailableTargets[0]         if(tmp->AddToTarget(Column,pixel,S1,S2,S3)         {          Remove tmpfrom AvailableTargets list          Add tmp to PossibleTargets list         t++  // target t has been shifted right         }       }     } while (keepTrying)    }   pixel += S1.RunLength   AdvanceS0/S1/S2/S3 }

AddToTarget is a function within the find targets module that determineswhether it is possible or not to add the specific run to the giventarget:

-   -   If the run is within the tolerance of target's starting        position, the run is directly related to the current target, and        can therefore be applied to it.    -   If the run starts before the target, we assume that the existing        target is still ok, but not relevant to the run. The target is        therefore left unchanged, and a return value of FALSE tells the        caller that the run was not applied. The caller can subsequently        check the run to see if it starts a whole new target of its own.    -   If the run starts after the target, we assume the target is no        longer a possible target. The state is changed to be NotATarget,        and a return value of TRUE is returned.

If the run is to be applied to the target, a specific action isperformed based on the current state and set of runs in S1, S2, and S3.The AddToTarget pseudocode is as follows:

MAX_TARGET_DELTA = 1 if (CurrentState != NothingKnown) {    if (pixel >StartPixel)    // run starts after target    {          diff = pixel −StartPixel          if (diff > MAX_TARGET_DELTA)          {            CurrentState = NotATarget             return TRUE          }   }    else    {          diff = StartPixel − pixel          if (diff >MAX_TARGET_DELTA)             return FALSE       } } runType =DetermineRunType(S1, S2, S3) EvaluateState(runType) StartPixel =currentPixel return TRUE

Types of pixel runs are identified in DetermineRunType is as follows:

Types of Pixel Runs Type How identified (S1 is always black)TargetBorder S1 = 40 < RunLength < 50 S2 = white run TargetCenter S1 =15 < RunLength < 26 S2 = white run with [RunLength < 12] S3 = black runwith [15 < RunLength < 26] TargetNumber S2 = white run with [RunLength<= 40]

The EvaluateState procedure takes action depending on the current stateand the run type.

The actions are shown as follows in tabular form:

Type of CurrentState Pixel Run Action NothingKnown TargetBorderDetectCount = 1 CurrentState = LeftOfCenter LeftOfCenter TargetBorderDetectCount++ if (DetectCount > 24) CurrentState = NotATargetTargetCenter DetectCount = 1 CurrentState = InCenter Column =currentColumn Pixel = currentPixel + S1.RunLength CurrentState =NotATarget InCenter TargetCenter DetectCount++ tmp = currentPixel +S1.RunLength if (tmp < Pixel) Pixel = tmp if (DetectCount > 13)CurrentState = NotATarget TargetBorder DetectCount = 1 CurrentState =RightOfCenter CurrentState = NotATarget RightOfCenter TargetBorderDetectCount++ if (DetectCount >= 12) CurrentState = NotATargetTargetNumber DetectCount = 1 CurrentState = InTargetNumber TargetNumber= (S2.RunLength+ 2)/6 CurrentState = NotATarget InTargetNumberTargetNumber tmp = (S2.RunLength+ 2)/6 if (tmp > TargetNumber)TargetNumber = tmp DetectCount++ if (DetectCount >= 12) CurrentState =NotATarget TargetBorder if (DetectCount >= 3) CurrentState = IsATargetelse CurrentState = NotATarget CurrentState = NotATarget IsATarget or —— NotATarget

Processing Targets

The located targets (in the LocatedTargets list) are stored in the orderthey were located. Depending on alternative Artcard rotation thesetargets will be in ascending pixel order or descending pixel order. Inaddition, the target numbers recovered from the targets may be in error.We may have also have recovered a false target. Before the clockmarkestimates can be obtained, the targets need to be processed to ensurethat invalid targets are discarded, and valid targets have targetnumbers fixed if in error (e.g. a damaged target number due to dirt).Two main steps are involved:

-   -   Sort targets into ascending pixel order    -   Locate and fix erroneous target numbers

The first step is simple. The nature of the target retrieval means thatthe data should already be sorted in either ascending pixel ordescending pixel. A simple swap sort ensures that if the 6 targets arealready sorted correctly a maximum of 14 comparisons is made with noswaps. If the data is not sorted, 14 comparisons are made, with 3 swaps.The following pseudocode shows the sorting process:

for (i = 0; i < TargetsFound−1; i++) {    oldTarget = LocatedTargets[i]   bestPixel = oldTarget->Pixel    best = i    j = i+1    while(j<TargetsFound)    {          if (LocatedTargets[j]-> Pixel <bestPixel)             best = j          j++    }    if (best != i) //move only if necessary          LocatedTargets[i] = LocatedTargets[best]         LocatedTargets[best] = oldTarget    } }

Locating and fixing erroneous target numbers is only slightly morecomplex. One by one, each of the N targets found is assumed to becorrect. The other targets are compared to this “correct” target and thenumber of targets that require change should target N be correct iscounted. If the number of changes is 0, then all the targets mustalready be correct. Otherwise the target that requires the fewestchanges to the others is used as the base for change. A change isregistered if a given target's target number and pixel position do notcorrelate when compared to the “correct” target's pixel position andtarget number. The change may mean updating a target's target number, orit may mean elimination of the target. It is possible to assume thatascending targets have pixels in ascending order (since they havealready been sorted).

kPixelFactor = 1/(55 * 3) bestTarget = 0 bestChanges = TargetsFound + 1for (i=0; i< TotalTargetsFound; i++) {    numberOfChanges = 0; fromPixel= (LocatedTargets[i])->Pixel fromTargetNumber =LocatedTargets[i].TargetNumber for (j=1; j< TotalTargetsFound; j++) {toPixel = LocatedTargets[j]->Pixel deltaPixel = toPixel − fromPixel if(deltaPixel >= 0)          deltaPixel +=         PIXELS_BETWEEN_TARGET_CENTRES/2    else          deltaPixel −=         PIXELS_BETWEEN_TARGET_CENTRES/2 targetNumber =deltaPixel *kPixelFactor targetNumber += fromTargetNumber if    (         (targetNumber < 1)||(targetNumber > 6)          ||         (targetNumber != LocatedTargets[j]->          TargetNumber)      )          numberOfChanges++ }    if (numberOfChanges <bestChanges)    { bestTarget = i bestChanges = numberOfChanges    }   if (bestChanges < 2)          break; }

In most cases this function will terminate with bestChanges=0, whichmeans no changes are required. Otherwise the changes need to be applied.The functionality of applying the changes is identical to counting thechanges (in the pseudocode above) until the comparison withtargetNumber. The change application is:

if ((targetNumber < 1)||(targetNumber > TARGETS_PER_BLOCK)) {   LocatedTargets[j] = NULL    TargetsFound−− } else {   LocatedTargets[j]-> TargetNumber = targetNumber }

At the end of the change loop, the LocatedTargets list needs to becompacted and all NULL targets removed.

At the end of this procedure, there may be fewer targets. Whatevertargets remain may now be used (at least 2 targets are required) tolocate the clockmarks and the data region.

Building Clockmark Estimates from Targets

As shown previously in FIG. 55, the upper region's first clockmark dot1126 is 55 dots away from the center of the first target 1124 (which isthe same as the distance between target centers). The center of theclockmark dots is a further 1 dot away, and the black border line 1123is a further 4 dots away from the first clockmark dot. The lowerregion's first clockmark dot is exactly 7 targets-distance away (7×55dots) from the upper region's first clockmark dot 1126.

It cannot be assumed that Targets 1 and 6 have been located, so it isnecessary to use the upper-most and lower-most targets, and use thetarget numbers to determine which targets are being used. It isnecessary at least 2 targets at this point. In addition, the targetcenters are only estimates of the actual target centers. It is to locatethe target center more accurately. The center of a target is white,surrounded by black. We therefore want to find the local maximum in bothpixel & column dimensions. This involves reconstructing the continuousimage since the maximum is unlikely to be aligned exactly on an integerboundary (our estimate).

Before the continuous image can be constructed around the target'scenter, it is necessary to create a better estimate of the 2 targetcenters. The existing target centers actually are the top leftcoordinate of the bounding box of the target center. It is a simpleprocess to go through each of the pixels for the area defining thecenter of the target, and find the pixel with the highest value. Theremay be more than one pixel with the same maximum pixel value, but theestimate of the center value only requires one pixel.

The pseudocode is straightforward, and is performed for each of the 2targets:

CENTER_WIDTH = CENTER_HEIGHT = 12 maxPixel = 0x00 for (i=0;i<CENTER_WIDTH; i++)    for (j=0; j<CENTER_HEIGHT; j++)    { p =GetPixel(column+i, pixel+j) if (p > maxPixel) { maxPixel = pcenterColumn = column + i centerPixel = pixel + j           }    }Target.Column = centerColumn Target.Pixel = centerPixel

At the end of this process the target center coordinates point to thewhitest pixel of the target, which should be within one pixel of theactual center. The process of building a more accurate position for thetarget center involves reconstructing the continuous signal for 7scanline slices of the target, 3 to either side of the estimated targetcenter. The 7 maximum values found (one for each of these pixeldimension slices) are then used to reconstruct a continuous signal inthe column dimension and thus to locate the maximum value in thatdimension.

// Given estimates column and pixel, determine a // betterColumn andbetterPixel as the center of // the target for (y=0; y<7; y++) {    for(x=0; x<7; x++)          samples[x] = GetPixel(column−3+y, pixel−3+x)   FindMax(samples, pos, maxVal)    reSamples[y] = maxVal    if (y == 3)         betterPixel = pos + pixel } FindMax(reSamples, pos, maxVal)betterColumn = pos + column

FindMax is a function that reconstructs the original 1 dimensionalsignal based sample points and returns the position of the maximum aswell as the maximum value found. The method of signalreconstruction/resampling used is the Lanczos3 windowed sinc function asshown in FIG. 76.

The Lanczos3 windowed sinc function takes 7 (pixel) samples from thedimension being reconstructed, centered around the estimated position X,i.e. at X−3, X−2, X−1, X, X+1, X+2, X+3. We reconstruct points from X−1to X+1, each at an interval of 0.1, and determine which point is themaximum. The position that is the maximum value becomes the new center.Due to the nature of the kernel, only 6 entries are required in theconvolution kernel for points between X and X+1. We use 6 points for X−1to X, and 6 points for X to X+1, requiring 7 points overall in order toget pixel values from X−1 to X+1 since some of the pixels required arethe same.

Given accurate estimates for the upper-most target from and lower-mosttarget to, it is possible to calculate the position of the firstclockmark dot for the upper and lower regions as follows:

TARGETS_PER_BLOCK = 6 numTargetsDiff = to.TargetNum − from.TargetNumdeltaPixel = (to.Pixel − from.Pixel) / numTargetsDiff deltaColumn =(to.Column − from.Column) / numTargetsDiff UpperClock.pixel = from.Pixel− (from.TargetNum*deltaPixel) UpperClock.column =from.Column−(from.TargetNum*deltaColumn) // Given the first dot of theupper clockmark, the // first dot of the lower clockmark isstraightforward. LowerClock.pixel     =      UpperClock.pixel     +   ((TARGETS_PER_BLOCK+1) * deltaPixel) LowerClock.column      =     UpperClock.column    +  ((TARGETS_PER_BLOCK+1) * deltaColumn)

This gets us to the first clockmark dot. It is necessary move the columnposition a further 1 dot away from the data area to reach the center ofthe clockmark. It is necessary to also move the pixel position a further4 dots away to reach the center of the border line. The pseudocodevalues for deltaColumn and deltaPixel are based on a 55 dot distance(the distance between targets), so these deltas must be scaled by 1/55and 4/55 respectively before being applied to the clockmark coordinates.This is represented as:

kDeltaDotFactor = 1/DOTS_BETWEEN_TARGET_CENTRES deltaColumn *=kDeltaDotFactor deltaPixel *= 4 * kDeltaDotFactor UpperClock.pixel −=deltaPixel UpperClock.column −= deltaColumn LowerClock.pixel +=deltaPixel LowerClock.column += deltaColumn

UpperClock and LowerClock are now valid clockmark estimates for thefirst clockmarks directly in line with the centers of the targets.

Setting Black and White Pixel/Dot Ranges

Before the data can be extracted from the data area, the pixel rangesfor black and white dots needs to be ascertained. The minimum andmaximum pixels encountered during the search for targets were stored inWhiteMin and BlackMax respectively, but these do not represent validvalues for these variables with respect to data extraction. They aremerely used for storage convenience. The following pseudocode shows themethod of obtaining good values for WhiteMin and BlackMax based on themin & max pixels encountered:

MinPixel = WhiteMin MaxPixel = BlackMax MidRange = (MinPixel + MaxPixel)/ 2 WhiteMin = MaxPixel − 105 BlackMax = MinPixel + 84 CurrentState =ExtractingBitImage

The ExtractingBitImage state is one where the data block has alreadybeen accurately located via the targets, and bit data is currently beingextracted one dot column at a time and written to the alternativeArtcard bit image. The following of data block clockmarks/borders givesaccurate dot recovery regardless of rotation, and thus the segmentbounds are ignored. Once the entire data block has been extracted (597columns of 48 bytes each; 595 columns of data+2 orientation columns),new segment bounds are calculated for the next data block based on thecurrent position. The state is changed to LookingForTargets.

Processing a given dot column involves two tasks:

-   -   The first task is to locate the specific dot column of data via        the clockmarks.    -   The second task is to run down the dot column gathering the bit        values, one bit per dot.

These two tasks can only be undertaken if the data for the column hasbeen read off the alternative Artcard and transferred to DRAM. This canbe determined by checking what scanline Process 1 is up to, andcomparing it to the clockmark columns. If the dot data is in DRAM we canupdate the clockmarks and then extract the data from the column beforeadvancing the clockmarks to the estimated value for the next dot column.The process overview is given in the following pseudocode, with specificfunctions explained hereinafter:

finishedBlock = FALSE if((UpperClock.column < Process1.CurrentScanLine)   &&    (LowerClock.column < Process1.CurrentScanLine)) {   DetermineAccurateClockMarks( )    DetermineDataInfo( )    if(CurrentDotColumn >= 0)          ExtractDataFromColumn( )   AdvanceClockMarks( )    if (CurrentDotColumn == FINAL_COLUMN)    {finishedBlock = TRUE currentState = LookingForTargetsSetBounds(UpperClock.pixel, LowerClock.pixel) BitImage += 256KBCurrentByte = 0 TargetsFound = 0    } } return finishedBlock

Locating the Dot Column

A given dot column needs to be located before the dots can be read andthe data extracted. This is accomplished by following theclockmarks/borderline along the upper and lower boundaries of the datablock. A software equivalent of a phase-locked-loop is used to ensurethat even if the clockmarks have been damaged, good estimations ofclockmark positions will be made. FIG. 77 illustrates an example datablock's top left which corner reveals that there are clockmarks 3 dotshigh 1166 extending out to the target area, a white row, and then ablack border line.

Initially, an estimation of the center of the first black clockmarkposition is provided (based on the target positions). We use the blackborder 1168 to achieve an accurate vertical position (pixel), and theclockmark e.g. 1166 to get an accurate horizontal position (column).These are reflected in the UpperClock and LowerClock positions.

The clockmark estimate is taken and by looking at the pixel data in itsvicinity, the continuous signal is reconstructed and the exact center isdetermined. Since we have broken out the two dimensions into a clockmarkand border, this is a simple one-dimensional process that needs to beperformed twice. However, this is only done every second dot column,when there is a black clockmark to register against. For the whiteclockmarks we simply use the estimate and leave it at that.Alternatively, we could update the pixel coordinate based on the bordereach dot column (since it is always present). In practice it issufficient to update both ordinates every other column (with the blackclockmarks) since the resolution being worked at is so fine. The processtherefore becomes:

// Turn the estimates of the clockmarks into accurate // positions onlywhen there is a black clockmark // (ie every 2nd dot column, startingfrom −8) if (Bit0(CurrentDotColumn) == 0)     // even column {   DetermineAccurateUpperDotCenter( )   DetermineAccurateLowerDotCenter( ) }

If there is a deviation by more than a given tolerance(MAX_CLOCKMARK_DEVIATION), the found signal is ignored and onlydeviation from the estimate by the maximum tolerance is allowed.

In this respect the functionality is similar to that of a phase-lockedloop. Thus DetermineAccurateUpperDotCenter is implemented via thefollowing pseudocode:

// Use the estimated pixel position of // the border to determine whereto look for // a more accurate clockmark center. The clockmark // is 3dots high so even if the estimated position // of the border is wrong,it won't affect the // fixing of the clockmark position.MAX_CLOCKMARK_DEVIATION = 0.5diff      =      GetAccurateColumn(UpperClock.column,         UpperClock.pixel+(3*PIXELS_PER_DOT)) diff −= UpperClock.columnif (diff > MAX_CLOCKMARK_DEVIATION)    diff = MAX_CLOCKMARK_DEVIATIONelse if (diff < −MAX_CLOCKMARK_DEVIATION)    diff =−MAX_CLOCKMARK_DEVIATION UpperClock.column += diff // Use the newlyobtained clockmark center to // determine a more accurate borderposition. diff = GetAccuratePixel(UpperClock.column, UpperClock.pixel)diff −= UpperClock.pixel if (diff > MAX_CLOCKMARK_DEVIATION)    diff =MAX_CLOCKMARK_DEVIATION else if (diff < −MAX_CLOCKMARK_DEVIATION)   diff = −MAX_CLOCKMARK_DEVIATION UpperClock.pixel += diff

DetermineAccurateLowerDotCenter is the same, except that the directionfrom the border to the clockmark is in the negative direction (−3 dotsrather than +3 dots).

GetAccuratePixel and GetAccurateColumn are functions that determine anaccurate dot center given a coordinate, but only from the perspective ofa single dimension. Determining accurate dot centers is a process ofsignal reconstruction and then finding the location where the minimumsignal value is found (this is different to locating a target center,which is locating the maximum value of the signal since the targetcenter is white, not black). The method chosen for signalreconstruction/resampling for this application is the Lanczos 3 windowedsinc function as previously discussed with reference to FIG. 76.

It may be that the clockmark or border has been damaged in someway—perhaps it has been scratched. If the new center value retrieved bythe resampling differs from the estimate by more than a toleranceamount, the center value is only moved by the maximum tolerance. If itis an invalid position, it should be close enough to use for dataretrieval, and future clockmarks will resynchronize the position.

Determining the Center of the First Data Dot and the Deltas toSubsequent Dots

Once an accurate UpperClock and LowerClock position has been determined,it is possible to calculate the center of the first data dot(CurrentDot), and the delta amounts to be added to that center positionin order to advance to subsequent dots in the column (DataDelta).

The first thing to do is calculate the deltas for the dot column. Thisis achieved simply by subtracting the UpperClock from the LowerClock,and then dividing by the number of dots between the two points. It ispossible to actually multiply by the inverse of the number of dots sinceit is constant for an alternative Artcard, and multiplying is faster. Itis possible to use different constants for obtaining the deltas in pixeland column dimensions. The delta in pixels is the distance between thetwo borders, while the delta in columns is between the centers of thetwo clockmarks. Thus the function DetermineDataInfo is two parts. Thefirst is given by the pseudocode:

kDeltaColumnFactor = 1 / (DOTS_PER_DATA_COLUMN + 2 + 2 − 1)kDeltaPixelFactor = 1 / (DOTS_PER_DATA_COLUMN + 5 + 5 − 1) delta =LowerClock.column − UpperClock.column DataDelta.column = delta *kDeltaColumnFactor delta = LowerClock.pixel − UpperClock.pixelDataDelta.pixel = delta * kDeltaPixelFactor

It is now possible to determine the center of the first data dot of thecolumn. There is a distance of 2 dots from the center of the clockmarkto the center of the first data dot, and 5 dots from the center of theborder to the center of the first data dot. Thus the second part of thefunction is given by the pseudocode:

CurrentDot.column = UpperClock.column + (2*DataDelta.column)CurrentDot.pixel = UpperClock.pixel + (5*DataDelta.pixel)

Running Down a Dot Column

Since the dot column has been located from the phase-locked looptracking the clockmarks, all that remains is to sample the dot column atthe center of each dot down that column. The variable CurrentDot pointsis determined to the center of the first dot of the current column. Wecan get to the next dot of the column by simply adding DataDelta (2additions: 1 for the column ordinate, the other for the pixel ordinate).A sample of the dot at the given coordinate (bi-linear interpolation) istaken, and a pixel value representing the center of the dot isdetermined. The pixel value is then used to determine the bit value forthat dot. However it is possible to use the pixel value in context withthe center value for the two surrounding dots on the same dot line tomake a better bit judgement.

We can be assured that all the pixels for the dots in the dot columnbeing extracted are currently loaded in DRAM, for if the two ends of theline (clockmarks) are in DRAM, then the dots between those twoclockmarks must also be in DRAM. Additionally, the data block height isshort enough (only 384 dots high) to ensure that simple deltas areenough to traverse the length of the line. One of the reasons the cardis divided into 8 data blocks high is that we cannot make the same rigidguarantee across the entire height of the card that we can about asingle data block.

The high level process of extracting a single line of data (48 bytes)can be seen in the following pseudocode. The dataBuffer pointerincrements as each byte is stored, ensuring that consecutive bytes andcolumns of data are stored consecutively.

bitCount = 8 curr = 0x00 //definitely black next = GetPixel(CurrentDot)for (i=0; i < DOTS_PER_DATA_COLUMN; i++) {  CurrentDot += DataDelta prev = curr  curr = next  next = GetPixel(CurrentDot)  bit =DetermineCenterDot(prev, curr, next)  byte = (byte << 1) | bit bitCount−−  if (bitCount == 0)  {   *(BitImage | CurrentByte) = byte  CurrentByte++   bitCount = 8  } }

The GetPixel function takes a dot coordinate (fixed point) and samples 4CCD pixels to arrive at a center pixel value via bilinear interpolation.

The DetermineCenterDot function takes the pixel values representing thedot centers to either side of the dot whose bit value is beingdetermined, and attempts to intelligently guess the value of that centerdot's bit value. From the generalized blurring curve of FIG. 64 thereare three common cases to consider:

-   -   The dot's center pixel value is lower than WhiteMin, and is        therefore definitely a black dot. The bit value is therefore        definitely 1.    -   The dot's center pixel value is higher than BlackMax, and is        therefore definitely a white dot. The bit value is therefore        definitely 0.    -   The dot's center pixel value is somewhere between BlackMax and        WhiteMin. The dot may be black, and it may be white. The value        for the bit is therefore in question. A number of schemes can be        devised to make a reasonable guess as to the value of the bit.        These schemes must balance complexity against accuracy, and also        take into account the fact that in some cases, there is no        guaranteed solution. In those cases where we make a wrong bit        decision, the bit's Reed-Solomon symbol will be in error, and        must be corrected by the Reed-Solomon decoding stage in Phase 2.

The scheme used to determine a dot's value if the pixel value is betweenBlackMax and WhiteMin is not too complex, but gives good results. Ituses the pixel values of the dot centers to the left and right of thedot in question, using their values to help determine a more likelyvalue for the center dot:

-   -   If the two dots to either side are on the white side of MidRange        (an average dot value), then we can guess that if the center dot        were white, it would likely be a “definite” white. The fact that        it is in the not-sure region would indicate that the dot was        black, and had been affected by the surrounding white dots to        make the value less sure. The dot value is therefore assumed to        be black, and hence the bit value is 1.    -   If the two dots to either side are on the black side of        MidRange, then we can guess that if the center dot were black,        it would likely be a “definite” black. The fact that it is in        the not-sure region would indicate that the dot was white, and        had been affected by the surrounding black dots to make the        value less sure. The dot value is therefore assumed to be white,        and hence the bit value is 0.    -   If one dot is on the black side of MidRange, and the other dot        is on the white side of MidRange, we simply use the center dot        value to decide. If the center dot is on the black side of        MidRange, we choose black (bit value 1). Otherwise we choose        white (bit value 0).

The logic is represented by the following:

if (pixel < WhiteMin) // definitely black bit = 0x01 else if (pixel >BlackMax) // definitely white bit = 0x00 else if ((prev > MidRange) &&(next> MidRange)) //prob black bit = 0x01 else if ((prev < MidRange) &&(next < MidRange)) //prob white bit = 0x00 else if (pixel < MidRange)bit = 0x01 else bit = 0x00

From this one can see that using surrounding pixel values can give agood indication of the value of the center dot's state. The schemedescribed here only uses the dots from the same row, but using a singledot line history (the previous dot line) would also be straightforwardas would be alternative arrangements.

Updating Clockmarks for the Next Column

Once the center of the first data dot for the column has beendetermined, the clockmark values are no longer needed. They areconveniently updated in readiness for the next column after the data hasbeen retrieved for the column. Since the clockmark direction isperpendicular to the traversal of dots down the dot column, it ispossible to use the pixel delta to update the column, and subtract thecolumn delta to update the pixel for both clocks:

UpperClock.column+=DataDelta.pixel

LowerClock.column+=DataDelta.pixel UpperClock.pixel−=DataDelta.columnLowerClock.pixel−=DataDelta.column

These are now the estimates for the next dot column.

Timing

The timing requirement will be met as long as DRAM utilization does notexceed 100%, and the addition of parallel algorithm timing multiplied bythe algorithm DRAM utilization does not exceed 100%. DRAM utilization isspecified relative to Process 1, which writes each pixel once in aconsecutive manner, consuming 9% of the DRAM bandwidth.

The timing as described in this section, shows that the DRAM is easilyable to cope with the demands of the alternative Artcard Readeralgorithm. The timing bottleneck will therefore be the implementation ofthe algorithm in terms of logic speed, not DRAM access. The algorithmshave been designed however, with simple architectures in mind, requiringa minimum number of logical operations for every memory cycle. From thispoint of view, as long as the implementation state machine or equivalentCPU/DSP architecture is able to perform as described in the followingsub-sections, the target speed will be met.

Locating the Targets

Targets are located by reading pixels within the bounds of a pixelcolumn. Each pixel is read once at most. Assuming a run-length encoderthat operates fast enough, the bounds on the location of targets ismemory access. The accesses will therefore be no worse than the timingfor Process 1, which means a 9% utilization of the DRAM bandwidth.

The total utilization of DRAM during target location (includingProcess 1) is therefore 18%, meaning that the target locator will alwaysbe catching up to the alternative Artcard image sensor pixel reader.

Processing the Targets

The timing for sorting and checking the target numbers is trivial. Thefinding of better estimates for each of the two target centers involves12 sets of 12 pixel reads, taking a total of 144 reads. However thefixing of accurate target centers is not trivial, requiring 2 sets ofevaluations. Adjusting each target center requires 8 sets of 20different 6-entry convolution kernels. Thus this totals 8×20×6multiply-accumulates=960. In addition, there are 7 sets of 7 pixels tobe retrieved, requiring 49 memory accesses. The total number per targetis therefore 144+960+49=1153, which is approximately the same number ofpixels in a column of pixels (1152). Thus each target evaluationconsumes the time taken by otherwise processing a row of pixels. For twotargets we effectively consume the time for 2 columns of pixels.

A target is positively identified on the first pixel column after thetarget number. Since there are 2 dot columns before the orientationcolumn, there are 6 pixel columns. The Target Location processeffectively uses up the first of the pixel columns, but the remaining 5pixel columns are not processed at all. Therefore the data area can belocated in ⅖ of the time available without impinging on any otherprocess time.

The remaining ⅗ of the time available is ample for the trivial task ofassigning the ranges for black and white pixels, a task that may take acouple of machine cycles at most.

Extracting Data

There are two parts to consider in terms of timing:

-   -   Getting accurate clockmarks and border values    -   Extracting dot values

Clockmarks and border values are only gathered every second dot column.However each time a clockmark estimate is updated to become moreaccurate, 20 different 6-entry convolution kernels must be evaluated. Onaverage there are 2 of these per dot column (there are 4 every 2dot-columns). Updating the pixel ordinate based on the border onlyrequires 7 pixels from the same pixel scanline Updating the columnordinate however, requires 7 pixels from different columns, hencedifferent scanlines. Assuming worst case scenario of a cache miss foreach scanline entry and 2 cache misses for the pixels in the samescanline, this totals 8 cache misses.

Extracting the dot information involves only 4 pixel reads per dot(rather than the average 9 that define the dot). Considering the dataarea of 1152 pixels (384 dots), at best this will save 72 cache reads byonly reading 4 pixel dots instead of 9. The worst case is a rotation of1° which is a single pixel translation every 57 pixels, which gives onlyslightly worse savings.

It can then be safely said that, at worst, we will be reading fewercache lines less than that consumed by the pixels in the data area. Theaccesses will therefore be no worse than the timing for Process 1, whichimplies a 9% utilization of the DRAM bandwidth. The total utilization ofDRAM during data extraction (including Process 1) is therefore 18%,meaning that the data extractor will always be catching up to thealternative Artcard image sensor pixel reader. This has implications forthe Process Targets process in that the processing of targets can beperformed by a relatively inefficient method if necessary, yet stillcatch up quickly during the extracting data process.

Phase 2—Decode Bit Image

Phase 2 is the non-real-time phase of alternative Artcard data recoveryalgorithm. At the start of Phase 2 a bit image has been extracted fromthe alternative Artcard. It represents the bits read from the dataregions of the alternative Artcard. Some of the bits will be in error,and perhaps the entire data is rotated 180° because the alternativeArtcard was rotated when inserted. Phase 2 is concerned with reliablyextracting the original data from this encoded bit image. There arebasically 3 steps to be carried out as illustrated in FIG. 79:

-   -   Reorganize the bit image, reversing it if the alternative        Artcard was inserted backwards    -   Unscramble the encoded data    -   Reed-Solomon decode the data from the bit image

Each of the 3 steps is defined as a separate process, and performedconsecutively, since the output of one is required as the input to thenext. It is straightforward to combine the first two steps into a singleprocess, but for the purposes of clarity, they are treated separatelyhere.

From a data/process perspective, Phase 2 has the structure asillustrated in FIG. 80. The timing of Processes 1 and 2 are likely to benegligible, consuming less than 1/1000^(th) of a second between them.Process 3 (Reed Solomon decode) consumes approximately 0.32 seconds,making this the total time required for Phase 2.

Reorganize the bit image, reversing it if necessary

The bit map in DRAM now represents the retrieved data from thealternative Artcard. However the bit image is not contiguous. It isbroken into 64 32 k chunks, one chunk for each data block. Each 32 kchunk contains only 28,656 useful bytes:

48 bytes from the leftmost Orientation Column28560 bytes from the data region proper48 bytes from the rightmost Orientation Column4112 unused bytes

The 2 MB buffer used for pixel data (stored by Process 1 of Phase 1) canbe used to hold the reorganized bit image, since pixel data is notrequired during Phase 2. At the end of the reorganization, a correctlyoriented contiguous bit image will be in the 2 MB pixel buffer, readyfor Reed-Solomon decoding.

If the card is correctly oriented, the leftmost Orientation Column willbe white and the rightmost Orientation Column will be black. If the cardhas been rotated 180°, then the leftmost Orientation Column will beblack and the rightmost Orientation Column will be white.

A simple method of determining whether the card is correctly oriented ornot, is to go through each data block, checking the first and last 48bytes of data until a block is found with an overwhelming ratio of blackto white bits. The following pseudocode demonstrates this, returningTRUE if the card is correctly oriented, and FALSE if it is not:

totalCountL = 0 totalCountR = 0 for (i=0; i<64; i++) { blackCountL = 0blackCountR = 0 currBuff = dataBuffer for (j=0; j<48; j++) { blackCountL+= CountBits(*currBuff) currBuff++   } currBuff += 28560 for (j=0; j<48;j++) { blackCountR += CountBits(*currBuff) currBuff++   } dataBuffer +=32k if (blackCountR > (blackCountL * 4))     return TRUE   if(blackCountL > (blackCountR * 4))     return FALSE   totalCountL +=blackCountL   totalCountR += blackCountR } return (totalCountR >totalCountL)

The data must now be reorganized, based on whether the card was orientedcorrectly or not. The simplest case is that the card is correctlyoriented. In this case the data only needs to be moved around a littleto remove the orientation columns and to make the entire datacontiguous. This is achieved very simply in situ, as described by thefollowing pseudocode:

DATA_BYTES_PER_DATA_BLOCK = 28560 to = dataBuffer from = dataBuffer +48) // left orientation column for (i=0; i<64; i++) { BlockMove(from,to, DATA_BYTES_PER_DATA_BLOCK) from += 32k to +=DATA_BYTES_PER_DATA_BLOCK }

The other case is that the data actually needs to be reversed. Thealgorithm to reverse the data is quite simple, but for simplicity,requires a 256-byte table Reverse where the value of Reverse[N] is abit-reversed N.

DATA_BYTES_PER_DATA_BLOCK = 28560 to = outBuffer for (i=0; i<64; i++) {from = dataBuffer + (i * 32k) from += 48 // skip orientation column from+= DATA_BYTES_PER_DATA_BLOCK − 1 // end of block for (j=0; j <DATA_BYTES_PER_DATA_BLOCK; j++) { *to++ = Reverse[*from] from−−   } }

The timing for either process is negligible, consuming less than1/1000^(th) of a second:

-   -   2 MB contiguous reads (2048/16×12 ns=1,536 ns)    -   2 MB effectively contiguous byte writes (2048/16×12 ns=1,536 ns)

Unscramble the Encoded Image

The bit image is now 1,827,840 contiguous, correctly oriented, butscrambled bytes. The bytes must be unscrambled to create the 7,168Reed-Solomon blocks, each 255 bytes long. The unscrambling process isquite straightforward, but requires a separate output buffer since theunscrambling cannot be performed in situ. FIG. 80 illustrates theunscrambling process conducted memory

The following pseudocode defines how to perform the unscramblingprocess:

groupSize = 255 numBytes = 1827840; inBuffer = scrambledBuffer;outBuffer = unscrambledBuffer; for (i=0; i<groupSize; i++)   for (j=i;j<numBytes; j+=groupSize)       outBuffer[j] = *inBuffer++

The timing for this process is negligible, consuming less than1/1000^(th) of a second:

-   -   2 MB contiguous reads (2048/16×12 ns=1,536 ns)    -   2 MB non-contiguous byte writes (2048×12 ns=24,576 ns)

At the end of this process the unscrambled data is ready forReed-Solomon decoding.

Reed Solomon Decode

The final part of reading an alternative Artcard is the Reed-Solomondecode process, where approximately 2 MB of unscrambled data is decodedinto approximately 1 MB of valid alternative Artcard data.

The algorithm performs the decoding one Reed-Solomon block at a time,and can (if desired) be performed in situ, since the encoded block islarger than the decoded block, and the redundancy bytes are stored afterthe data bytes.

The first 2 Reed-Solomon blocks are control blocks, containinginformation about the size of the data to be extracted from the bitimage. This meta-information must be decoded first, and the resultantinformation used to decode the data proper. The decoding of the dataproper is simply a case of decoding the data blocks one at a time.Duplicate data blocks can be used if a particular block fails to decode.

The highest level of the Reed-Solomon decode is set out in pseudocode:

// Constants for Reed Solomon decode sourceBlockLength = 255;destBlockLength = 127; numControlBlocks = 2; // Decode the controlinformation if (! GetControlData(source, destBlocks, lastBlock))  return error destBytes = ((destBlocks−1) * destBlockLength) +lastBlock offsetToNextDuplicate = destBlocks * sourceBlockLength // Skipthe control blocks and position at data source += numControlBlocks *sourceBlockLength // Decode each of the data blocks, trying //duplicates as necessary blocksInError = 0; for (i=0; i<destBlocks; i++){   found = DecodeBlock(source, dest); if (! found)   { duplicate =source + offsetToNextDuplicate while ((! found) &&(duplicate<sourceEnd))       { found = DecodeBlock(duplicate, dest)duplicate += offsetToNextDuplicate       }   }   if (! found)      blocksInError++   source += sourceBlockLength   dest +=destBlockLength } return destBytes and blocksInError

DecodeBlock is a standard Reed Solomon block decoder using m=8 and t=64.

The GetControlData function is straightforward as long as there are nodecoding errors. The function simply calls DecodeBlock to decode onecontrol block at a time until successful. The control parameters canthen be extracted from the first 3 bytes of the decoded data (destBlocksis stored in the bytes 0 and 1, and lastBlock is stored in byte 2). Ifthere are decoding errors the function must traverse the 32 sets of 3bytes and decide which is the most likely set value to be correct. Onesimple method is to find 2 consecutive equal copies of the 3 bytes, andto declare those values the correct ones. An alternative method is tocount occurrences of the different sets of 3 bytes, and announce themost common occurrence to be the correct one.

The time taken to Reed-Solomon decode depends on the implementation.While it is possible to use a dedicated core to perform the Reed-Solomondecoding process (such as LSI Logic's L64712), it is preferable toselect a CPU/DSP combination that can be more generally used throughoutthe embedded system (usually to do something with the decoded data)depending on the application. Of course decoding time must be fastenough with the CPU/DSP combination.

The L64712 has a throughput of 50 Mbits per second (around 6.25 MB persecond), so the time is bound by the speed of the Reed-Solomon decoderrather than the maximum 2 MB read and 1 MB write memory access time. Thetime taken in the worst case (all 2 MB requires decoding) is thus 2/6.25s=approximately 0.32 seconds. Of course, many further refinements arepossible including the following:

The blurrier the reading environment, the more a given dot is influencedby the surrounding dots. The current reading algorithm of the preferredembodiment has the ability to use the surrounding dots in the samecolumn in order to make a better decision about a dot's value. Since theprevious column's dots have already been decoded, a previous column dothistory could be useful in determining the value of those dots whosepixel values are in the not-sure range.

A different possibility with regard to the initial stage is to remove itentirely, make the initial bounds of the data blocks larger thannecessary and place greater intelligence into the ProcessingTargetsfunctions. This may reduce overall complexity. Care must be taken tomaintain data block independence.

Further the control block mechanism can be made more robust:

-   -   The control block could be the first and last blocks rather than        make them contiguous (as is the case now). This may give greater        protection against certain pathological damage scenarios.    -   The second refinement is to place an additional level of        redundancy/error detection into the control block structure to        be used if the Reed-Solomon decode step fails. Something as        simple as parity might improve the likelihood of control        information if the Reed-Solomon stage fails.

Phase 5 Running the Vark Script

The overall time taken to read the Artcard 9 and decode it is thereforeapproximately 2.15 seconds. The apparent delay to the user is actuallyonly 0.65 seconds (the total of Phases 3 and 4), since the Artcard stopsmoving after 1.5 seconds.

Once the Artcard is loaded, the Artvark script must be interpreted,Rather than run the script immediately, the script is only run upon thepressing of the ‘Print’ button 13 (FIG. 1). The taken to run the scriptwill vary depending on the complexity of the script, and must be takeninto account for the perceived delay between pressing the print buttonand the actual print button and the actual printing.

As noted previously, the VLIW processor 74 is a digital processingsystem that accelerates computationally expensive Vark functions. Thebalance of functions performed in software by the CPU core 72, and inhardware by the VLIW processor 74 will be implementation dependent. Thegoal of the VLIW processor 74 is to assist all Artcard styles to executein a time that does not seem too slow to the user. As CPUs become fasterand more powerful, the number of functions requiring hardwareacceleration becomes less and less. The VLIW processor has a microcodedALU sub-system that allows general hardware speed up of the followingtime-critical functions.

1) Image access mechanisms for general software processing2) Image convolver.3) Data driven image warper4) Image scaling5) Image tessellation6) Affine transform7) Image compositor8) Color space transform9) Histogram collector

10) Illumination of the Image

11) Brush stamper12) Histogram collector13) CCD image to internal image conversion14) Construction of image pyramids (used by warper & for brushing)

The following table summarizes the time taken for each Vark operation ifimplemented in the ALU model. The method of implementing the functionusing the ALU model is described hereinafter.

1500 * 1000 image Operation Speed of Operation 1 channel 3 channelsImage composite 1 cycle per output pixel 0.015 s 0.045 s Image convolvek/3 cycles per output pixel (k = kernel size) 3 × 3 convolve 0.045 s0.135 s 5 × 5 convolve 0.125 s 0.375 s 7 × 7 convolve 0.245 s 0.735 sImage warp 8 cycles per pixel 0.120 s 0.360 s Histogram collect 2 cyclesper pixel 0.030 s 0.090 s Image Tessellate ⅓ cycle per pixel 0.005 s0.015 s Image sub-pixel Translate 1 cycle per output pixel — — Colorlookup replace ½ cycle per pixel 0.008 s 0.023 Color space transform 8cycles per pixel 0.120 s 0.360 s Convert CCD image to 4 cycles peroutput pixel  0.06 s  0.18 s internal image (including color convert &scale) Construct image pyramid 1 cycle per input pixel 0.015 s 0.045 sScale Maximum of: 0.015 s 0.045 s 2 cycles per input pixel (minimum)(minimum) 2 cycles per output pixel 2 cycles per output pixel (scaled inX only) Affine transform 2 cycles per output pixel  0.03 s  0.09 s Brushrotate/translate and ? composite Tile Image 4-8 cycles per output pixel0.015 s to 0.030 s 0.060 s to 0.120 s to for 4 channels (Lab, texture)Illuminate image Cycles per pixel Ambient only ½ 0.008 s 0.023 sDirectional light  1 0.015 s 0.045 s Directional (bm)  6  0.09 s  0.27 sOmni light  6  0.09 s  0.27 s Omni (bm)  9 0.137 s  0.41 s Spotlight  90.137 s  0.41 s Spotlight (bm) 12  0.18 s  0.54 s (bm) = bumpmap

For example, to convert a CCD image, collect histogram & performlookup-color replacement (for image enhancement) takes: 9+2+0.5 cyclesper pixel, or 11.5 cycles. For a 1500×1000 image that is 172,500,000, orapproximately 0.2 seconds per component, or 0.6 seconds for all 3components. Add a simple warp, and the total comes to 0.6+0.36, almost 1second.

Image Convolver

A convolve is a weighted average around a center pixel. The average maybe a simple sum, a sum of absolute values, the absolute value of a sum,or sums truncated at 0.

The image convolver is a general-purpose convolver, allowing a varietyof functions to be implemented by varying the values within avariable-sized coefficient kernel. The kernel sizes supported are 3×3,5×5 and 7×7 only.

Turning now to FIG. 82, there is illustrated 340 an example of theconvolution process. The pixel component values fed into the convolverprocess 341 come from a Box Read Iterator 342. The Iterator 342 providesthe image data row by row, and within each row, pixel by pixel. Theoutput from the convolver 341 is sent to a Sequential Write Iterator344, which stores the resultant image in a valid image format.

A Coefficient Kernel 346 is a lookup table in DRAM. The kernel isarranged with coefficients in the same order as the Box Read Iterator342. Each coefficient entry is 8 bits. A simple Sequential Read Iteratorcan be used to index into the kernel 346 and thus provide thecoefficients. It simulates an image with ImageWidth equal to the kernelsize, and a Loop option is set so that the kernel would continuously beprovided.

One form of implementation of the convolve process on an ALU unit is asillustrated in FIG. 81. The following constants are set by software:

Constant Value K₁ Kernel size (9, 25, or 49)

The control logic is used to count down the number of multiply/adds perpixel. When the count (accumulated in Latch₂) reaches 0, the controlsignal generated is used to write out the current convolve value (fromLatch₁) and to reset the count. In this way, one control logic block canbe used for a number of parallel convolve streams.

Each cycle the multiply ALU can perform one multiply/add to incorporatethe appropriate part of a pixel. The number of cycles taken to sum upall the values is therefore the number of entries in the kernel. Sincethis is compute bound, it is appropriate to divide the image intomultiple sections and process them in parallel on different ALU units.

On a 7×7 kernel, the time taken for each pixel is 49 cycles, or 490 ns.Since each cache line holds 32 pixels, the time available for memoryaccess is 12,740 ns. ((32−7+1)×490 ns). The time taken to read 7 cachelines and write 1 is worse case 1,120 ns (8*140 ns, all accesses to sameDRAM bank). Consequently it is possible to process up to 10 pixels inparallel given unlimited resources. Given a limited number of ALUs it ispossible to do at best 4 in parallel. The time taken to thereforeperform the convolution using a 7×7 kernel is 0.18375 seconds(1500*1000*490 ns/4=183,750,000 ns).

On a 5×5 kernel, the time taken for each pixel is 25 cycles, or 250 ns.Since each cache line holds 32 pixels, the time available for memoryaccess is 7,000 ns. ((32-5+1)×250 ns). The time taken to read 5 cachelines and write 1 is worse case 840 ns (6*140 ns, all accesses to sameDRAM bank). Consequently it is possible to process up to 7 pixels inparallel given unlimited resources. Given a limited number of ALUs it ispossible to do at best 4. The time taken to therefore perform theconvolution using a 5×5 kernel is 0.09375 seconds (1500*1000*250ns/4=93,750,000 ns).

On a 3×3 kernel, the time taken for each pixel is 9 cycles, or 90 ns.Since each cache line holds 32 pixels, the time available for memoryaccess is 2,700 ns. ((32-3+1)×90 ns). The time taken to read 3 cachelines and write 1 is worse case 560 ns (4*140 ns, all accesses to sameDRAM bank). Consequently it is possible to process up to 4 pixels inparallel given unlimited resources. Given a limited number of ALUs andRead/Write Iterators it is possible to do at best 4. The time taken totherefore perform the convolution using a 3×3 kernel is 0.03375 seconds(1500*1000*90 ns/4=33,750,000 ns).

Consequently each output pixel takes kernelsize/3 cycles to compute. Theactual timings are summarised in the following table:

Time taken Time to process Time to Process Kernel to calculate 1 channelat 3 channels at size output pixel 1500 × 1000 1500 × 1000 3 × 3 (9) 3cycles 0.045 seconds 0.135 seconds 5 × 5 (25) 8⅓ cycles 0.125 seconds0.375 seconds 7 × 7 (49) 16⅓ cycles 0.245 seconds 0.735 seconds

Image Compositor

Compositing is to add a foreground image to a background image using amatte or a channel to govern the appropriate proportions of backgroundand foreground in the final image. Two styles of compositing arepreferably supported, regular compositing and associated compositing.The rules for the two styles are:

Regular composite: new Value=Foreground+(Background−Foreground)a

Associated composite: new value=Foreground+(1−a)Background

The difference then, is that with associated compositing, the foregroundhas been pre-multiplied with the matte, while in regular compositing ithas not. An example of the compositing process is as illustrated in FIG.83.

The alpha channel has values from 0 to 255 corresponding to the range 0to 1.

Regular Composite

A regular composite is implemented as:

Foreground+(Background−Foreground)*α/255

The division by X/255 is approximated by 257X/65536. An implementationof the compositing process is shown in more detail in FIG. 84, where thefollowing constant is set by software:

Constant Value K₁ 257

Since 4 Iterators are required, the composite process takes 1 cycle perpixel, with a utilization of only half of the ALUs. The compositeprocess is only run on a single channel. To composite a 3-channel imagewith another, the compositor must be run 3 times, once for each channel.

The time taken to composite a full size single channel is 0.015 s(1500*1000*1*10 ns), or 0.045 s to composite all 3 channels.

To approximate a divide by 255 it is possible to multiply by 257 andthen divide by 65536. It can also be achieved by a single add (256*x+x)and ignoring (except for rounding purposes) the final 16 bits of theresult.

As shown in FIG. 42, the compositor process requires 3 Sequential ReadIterators 351-353 and 1 Sequential Write Iterator 355, and isimplemented as microcode using a Adder ALU in conjunction with amultiplier ALU. Composite time is 1 cycle (10 ns) per-pixel. Differentmicrocode is required for associated and regular compositing, althoughthe average time per pixel composite is the same.

The composite process is only run on a single channel. To composite one3-channel image with another, the compositor must be run 3 times, oncefor each channel. As the a channel is the same for each composite, itmust be read each time. However it should be noted that to transfer(read or write) 4×32 byte cache-lines in the best case takes 320 ns. Thepipeline gives an average of 1 cycle per pixel composite, taking 32cycles or 320 ns (at 100 MHz) to composite the 32 pixels, so the achannel is effectively read for free. An entire channel can therefore becomposited in:

1500/32*1000*320 ns=15,040,000 ns=0.015 seconds.

The time taken to composite a full size 3 channel image is therefore0.045 seconds.

Construct Image Pyramid

Several functions, such as warping, tiling and brushing, require theaverage value of a given area of pixels. Rather than calculate the valuefor each area given, these functions preferably make use of an imagepyramid. As illustrated previously in FIG. 33, an image pyramid 360 iseffectively a multi-resolution pixelmap. The original image is a 1:1representation. Sub-sampling by 2:1 in each dimension produces an image¼ the original size. This process continues until the entire image isrepresented by a single pixel.

An image pyramid is constructed from an original image, and consumes ⅓of the size taken up by the original image (¼+ 1/16+ 1/64+ . . . ). Foran original image of 1500×1000 the corresponding image pyramid isapproximately ½ MB

The image pyramid can be constructed via a 3×3 convolve performed on 1in 4 input image pixels advancing the center of the convolve kernel by 2pixels each dimension. A 3×3 convolve results in higher accuracy thansimply averaging 4 pixels, and has the added advantage that coordinateson different pyramid levels differ only by shifting 1 bit per level.

The construction of an entire pyramid relies on a software loop thatcalls the pyramid level construction function once for each level of thepyramid.

The timing to produce 1 level of the pyramid is 9/4*¼ of the resolutionof the input image since we are generating an image ¼ of the size of theoriginal. Thus for a 1500×1000 image:

Timing to produce level 1 of pyramid= 9/4*750*500=843,750 cycles

Timing to produce level 2 of pyramid= 9/4*375*250=210,938 cycles

Timing to produce level 3 of pyramid= 9/4*188*125=52,735 cycles

Etc.

The total time is ¾ cycle per original image pixel (image pyramid is ⅓of original image size, and each pixel takes 9/4 cycles to becalculated, i.e. ⅓* 9/4=¾). In the case of a 1500×1000 image is1,125,000 cycles (at 100 MHz), or 0.011 seconds. This timing is for asingle color channel, 3 color channels require 0.034 seconds processingtime.

General Data Driven Image Warper

The ACP 31 is able to carry out image warping manipulations of the inputimage. The principles of image warping are well-known in theory. Onethorough text book reference on the process of warping is “Digital ImageWarping” by George Wolberg published in 1990 by the IEEE ComputerSociety Press, Los Alamitos, Calif. The warping process utilizes a warpmap which forms part of the data fed in via Artcard 9. The warp map canbe arbitrarily dimensioned in accordance with requirements and providesinformation of a mapping of input pixels to output pixels.Unfortunately, the utilization of arbitrarily sized warp maps presents anumber of problems which must be solved by the image warper.

Turning to FIG. 85, a warp map 365, having dimensions A×B comprisesarray values of a certain magnitude (for example 8 bit values from0-255) which set out the coordinate of a theoretical input image whichmaps to the corresponding “theoretical” output image having the samearray coordinate indices. Unfortunately, any output image e.g. 366 willhave its own dimensions C×D which may further be totally different froman input image which may have its own dimensions E×F. Hence, it isnecessary to facilitate the remapping of the warp map 365 so that it canbe utilised for output image 366 to determine, for each output pixel,the corresponding area or region of the input image 367 from which theoutput pixel color data is to be constructed. For each output pixel inoutput image 366 it is necessary to first determine a corresponding warpmap value from warp map 365. This may include the need to bilinearlyinterpolate the surrounding warp map values when an output image pixelmaps to a fractional position within warp map table 365. The result ofthis process will give the location of an input image pixel in a“theoretical” image which will be dimensioned by the size of each datavalue within the warp map 365. These values must be re-scaled so as tomap the theoretical image to the corresponding actual input image 367.

In order to determine the actual value and output image pixel shouldtake so as to avoid aliasing effects, adjacent output image pixelsshould be examined to determine a region of input image pixels 367 whichwill contribute to the final output image pixel value. In this respect,the image pyramid is utilised as will become more apparent hereinafter.

The image warper performs several tasks in order to warp an image.

-   -   Scale the warp map to match the output image size.    -   Determine the span of the region of input image pixels        represented in each output pixel.    -   Calculate the final output pixel value via tri-linear        interpolation from the input image pyramid

Scale Warp Map

As noted previously, in a data driven warp, there is the need for a warpmap that describes, for each output pixel, the center of a correspondinginput image map. Instead of having a single warp map as previouslydescribed, containing interleaved x and y value information, it ispossible to treat the X and Y coordinates as separate channels.

Consequently, preferably there are two warp maps: an X warp map showingthe warping of X coordinates, and a Y warp map, showing the warping ofthe Y coordinates. As noted previously, the warp map 365 can have adifferent spatial resolution than the image they being scaled (forexample a 32×32 warp-map 365 may adequately describe a warp for a1500×1000 image 366). In addition, the warp maps can be represented by 8or 16 bit values that correspond to the size of the image being warped.

There are several steps involved in producing points in the input imagespace from a given warp map:

1. Determining the corresponding position in the warp map for the outputpixel

2. Fetch the values from the warp map for the next step (this canrequire scaling in the resolution domain if the warp map is only 8 bitvalues)

3. Bi-linear interpolation of the warp map to determine the actual value

4. Scaling the value to correspond to the input image domain

The first step can be accomplished by multiplying the current X/Ycoordinate in the output image by a scale factor (which can be differentin X & Y). For example, if the output image was 1500×1000, and the warpmap was 150×100, we scale both X & Y by 1/10.

Fetching the values from the warp map requires access to 2 Lookuptables. One Lookup table indexes into the X warp-map, and the otherindexes into the Y warp-map. The lookup table either reads 8 or 16 bitentries from the lookup table, but always returns 16 bit values(clearing the high 8 bits if the original values are only 8 bits).

The next step in the pipeline is to bi-linearly interpolate thelooked-up warp map values.

Finally the result from the bi-linear interpolation is scaled to placeit in the same domain as the image to be warped. Thus, if the warp maprange was 0-255, we scale X by 1500/255, and Y by 1000/255.

The interpolation process is as illustrated in FIG. 86 with thefollowing constants set by software:

Constant Value K₁ Xscale (scales 0-ImageWidth to 0-WarpmapWidth) K₂Yscale (scales 0-ImageHeight to 0-WarpmapHeight) K₃ XrangeScale (scaleswarpmap range (eg 0-255) to 0-ImageWidth) K₄ YrangeScale (scales warpmaprange (eg 0-255) to 0-ImageHeight)The following lookup table is used:

Lookup Size Details LU₁ and WarpmapWidth × Warpmap lookup. LU₂WarpmapHeight Given [X, Y] the 4 entries required for bi-linearinterpolation are returned. Even if entries are only 8 bit, they arereturned as 16 bit (high 8 bits 0). Transfer time is 4 entries at 2bytes per entry. Total time is 8 cycles as 2 lookups are used.

Span Calculation

The points from the warp map 365 locate centers of pixel regions in theinput image 367. The distance between input image pixels of adjacentoutput image pixels will indicate the size of the regions, and thisdistance can be approximated via a span calculation.

Turning to FIG. 87, for a given current point in the warp map P1, theprevious point on the same line is called P0, and the previous line'spoint at the same position is called P2. We determine the absolutedistance in X & Y between P1 and P0, and between P1 and P2. The maximumdistance in X or Y becomes the span which will be a square approximationof the actual shape.

Preferably, the points are processed in a vertical strip output order,PO is the previous point on the same line within a strip, and when P1 isthe first point on line within a strip, then PO refers to the last pointin the previous strip's corresponding line. P2 is the previous line'spoint in the same strip, so it can be kept in a 32-entry history buffer.The basic of the calculate span process are as illustrated in FIG. 88with the details of the process as illustrated in FIG. 89.

The following DRAM FIFO is used:

Lookup Size Details FIFO₁ 8 ImageWidth bytes. P2 history/lookup (both X& Y in same [ImageWidth × 2 FIFO) entries at 32 bits per P1 is put intothe FIFO and taken out entry] again at the same pixel on the followingrow as P2. Transfer time is 4 cycles (2 × 32 bits, with 1 cycle per 16bits)

Since a 32 bit precision span history is kept, in the case of a 1500pixel wide image being warped 12,000 bytes temporary storage isrequired.

Calculation of the span 364 uses 2 Adder ALUs (1 for span calculation, 1for looping and counting for P0 and P2 histories) takes 7 cycles asfollows:

Cycle Action 1 A = ABS(P1_(x) − P2_(x)) Store P1_(x) in P2_(x) history 2B = ABS(P1_(x) − P0_(x)) Store P1_(x) in P0_(x) history 3 A = MAX(A, B)4 B = ABS(P1_(y) − P2_(y)) Store P1_(y) in P2_(y) history 5 A = MAX(A,B) 6 B = ABS(P1_(y) − P0_(y)) Store P1_(y) in P0_(y) history 7 A =MAX(A, B)

The history buffers 365, 366 are cached DRAM. The ‘Previous Line’ (forP2 history) buffer 366 is 32 entries of span-precision. The ‘PreviousPoint’ (for PO history). Buffer 365 requires 1 register that is usedmost of the time (for calculation of points 1 to 31 of a line in astrip), and a DRAM buffered set of history values to be used in thecalculation of point 0 in a strip's line.

32 bit precision in span history requires 4 cache lines to hold P2history, and 2 for PO history. PO's history is only written and read outonce every 8 lines of 32 pixels to a temporary storage space of(ImageHeight*4) bytes. Thus a 1500 pixel high image being warpedrequires 6000 bytes temporary storage, and a total of 6 cache lines.

Tri-Linear Interpolation

Having determined the center and span of the area from the input imageto be averaged, the final part of the warp process is to determine thevalue of the output pixel. Since a single output pixel couldtheoretically be represented by the entire input image, it ispotentially too time-consuming to actually read and average the specificarea of the input image contributing to the output pixel. Instead, it ispossible to approximate the pixel value by using an image pyramid of theinput image.

If the span is 1 or less, it is necessary only to read the originalimage's pixels around the given coordinate, and perform bi-linearinterpolation. If the span is greater than 1, we must read twoappropriate levels of the image pyramid and perform tri-linearinterpolation. Performing linear interpolation between two levels of theimage pyramid is not strictly correct, but gives acceptable results (iterrs on the side of blurring the resultant image).

Turning to FIG. 90, generally speaking, for a given span ‘s’, it isnecessary to read image pyramid levels given by ln₂s (370) and ln₂s+1(371). Ln₂s is simply decoding the highest set bit of s. We mustbi-linear interpolate to determine the value for the pixel value on eachof the two levels 370,371 of the pyramid, and then interpolate betweenlevels.

As shown in FIG. 91, it is necessary to first interpolate in X and Y foreach pyramid level before interpolating between the pyramid levels toobtain a final output value 373.

The image pyramid address mode issued to generate addresses for pixelcoordinates at (x, y) on pyramid level s & s+1. Each level of the imagepyramid contains pixels sequential in x. Hence, reads in x are likely tobe cache hits.

Reasonable cache coherence can be obtained as local regions in theoutput image are typically locally coherent in the input image (perhapsat a different scale however, but coherent within the scale). Since itis not possible to know the relationship between the input and outputimages, we ensure that output pixels are written in a vertical strip(via a Vertical-Strip Iterator) in order to best make use of cachecoherence.

Tri-linear interpolation can be completed in as few as 2 cycles onaverage using 4 multiply ALUs and all 4 adder ALUs as a pipeline andassuming no memory access required. But since all the interpolationvalues are derived from the image pyramids, interpolation speed iscompletely dependent on cache coherence (not to mention the other unitsare busy doing warp-map scaling and span calculations). As many cachelines as possible should therefore be available to the image-pyramidreading. The best speed will be 8 cycles, using 2 Multiply ALUs.

The output pixels are written out to the DRAM via a Vertical-Strip WriteIterator that uses 2 cache lines. The speed is therefore limited to aminimum of 8 cycles per output pixel. If the scaling of the warp maprequires 8 or fewer cycles, then the overall speed will be unchanged.Otherwise the throughput is the time taken to scale the warp map. Inmost cases the warp map will be scaled up to match the size of thephoto.

Assuming a warp map that requires 8 or fewer cycles per pixel to scale,the time taken to convert a single color component of image is therefore0.12 s (1500*1000*8 cycles*10 ns per cycle).

Histogram Collector

The histogram collector is a microcode program that takes an imagechannel as input, and produces a histogram as output. Each of achannel's pixels has a value in the range 0-255. Consequently there are256 entries in the histogram table, each entry 32 bits—large enough tocontain a count of an entire 1500×1000 image.

As shown in FIG. 92, since the histogram represents a summary of theentire image, a Sequential Read Iterator 378 is sufficient for theinput. The histogram itself can be completely cached, requiring 32 cachelines (1K).

The microcode has two passes: an initialization pass which sets all thecounts to zero, and then a “count” stage that increments the appropriatecounter for each pixel read from the image. The first stage requires theAddress Unit and a single Adder ALU, with the address of the histogramtable 377 for initialising.

Address Unit Relative Microcode A = Base address Address of histogramAdder Unit 1 0 Write 0 to Out1 = A A + (Adder1.Out1 << 2) A = A − 1 BNZ0 1 Rest of processing Rest of processing

The second stage processes the actual pixels from the image, and uses 4Adder ALUs:

Adder 1 Adder 2 Adder 3 Adder 4 Address Unit 1 A = 0 A = −1 2 Out1 = A A= Adder1.Out1 A = Adr.Out1 A = A + 1 Out1 = Read 4 bytes from: BZ A =pixel Z = pixel − (A + (Adder1.Out1 << 2)) 2 Adder1.Out1 3 Out1 = A Out1= A Out1 = A Write Adder4.Out1 to: A = Adder3.Out1 (A + (Adder2.Out <<2) 4 Write Adder4.Out1 to: (A + (Adder2.Out << 2) Flush caches

The Zero flag from Adder2 cycle 2 is used to stay at microcode address 2for as long as the input pixel is the same. When it changes, the newcount is written out in microcode address 3, and processing resumes atmicrocode address 2. Microcode address 4 is used at the end, when thereare no more pixels to be read.

Stage 1 takes 256 cycles, or 2560 ns. Stage 2 varies according to thevalues of the pixels. The worst case time for lookup table replacementis 2 cycles per image pixel if every pixel is not the same as itsneighbor. The time taken for a single color lookup is 0.03 s(1500×1000×2 cycle per pixel×10 ns per cycle=30,000,000 ns). The timetaken for 3 color components is 3 times this amount, or 0.09 s.

Color Transform

Color transformation is achieved in two main ways:

Lookup table replacement

Color space conversion

Lookup Table Replacement

As illustrated in FIG. 86, one of the simplest ways to transform thecolor of a pixel is to encode an arbitrarily complex transform functioninto a lookup table 380. The component color value of the pixel is usedto lookup 381 the new component value of the pixel. For each pixel readfrom a Sequential Read Iterator, its new value is read from the NewColor Table 380, and written to a Sequential Write Iterator 383. Theinput image can be processed simultaneously in two halves to makeeffective use of memory bandwidth. The following lookup table is used:

Lookup Size Details LU₁ 256 entries Replacement[X] 8 bits per entryTable indexed by the 8 highest significant bits of X. Resultant 8 bitstreated as fixed point 0:8

The total process requires 2 Sequential Read Iterators and 2 SequentialWrite iterators. The 2 New Color Tables require 8 cache lines each tohold the 256 bytes (256 entries of 1 byte).

The average time for lookup table replacement is therefore ½ cycle perimage pixel. The time taken for a single color lookup is 0.0075 s(1500×1000×½ cycle per pixel×10 ns per cycle=7,500,000 ns). The timetaken for 3 color components is 3 times this amount, or 0.0225 s. Eachcolor component has to be processed one after the other under control ofsoftware.

Color Space Conversion

Color Space conversion is only required when moving between colorspaces. The CCD images are captured in RGB color space, and printingoccurs in CMY color space, while clients of the ACP 31 likely processimages in the Lab color space. All of the input color space channels aretypically required as input to determine each output channel's componentvalue. Thus the logical process is as illustrated 385 in FIG. 94.

Simply, conversion between Lab, RGB, and CMY is fairly straightforward.However the individual color profile of a particular device can varyconsiderably. Consequently, to allow future CCDs, inks, and printers,the ACP 31 performs color space conversion by means of tri-linearinterpolation from color space conversion lookup tables.

Color coherence tends to be area based rather than line based. To aidcache coherence during tri-linear interpolation lookups, it is best toprocess an image in vertical strips. Thus the read 386-388 and write 389iterators would be Vertical-Strip Iterators.

Tri-Linear Color Space Conversion

For each output color component, a single 3D table mapping the inputcolor space to the output color component is required. For example, toconvert CCD images from RGB to Lab, 3 tables calibrated to the physicalcharacteristics of the CCD are required:

RGB->L

RGB->a

RGB->b

To convert from Lab to CMY, 3 tables calibrated to the physicalcharacteristics of the ink/printer are required:

Lab->C

Lab->M

Lab->Y

The 8-bit input color components are treated as fixed-point numbers(3:5) in order to index into the conversion tables. The 3 bits ofinteger give the index, and the 5 bits of fraction are used forinterpolation. Since 3 bits gives 8 values, 3 dimensions gives 512entries (8×8×8). The size of each entry is 1 byte, requiring 512 bytesper table.

The Convert Color Space process can therefore be implemented as shown inFIG. 95 and the following lookup table is used:

Lookup Size Details LU₁ 8 × 8 × 8 entries Convert[X, Y, Z] 512 entriesTable indexed by the 3 highest bits of X, Y, 8 bits per entry and Z. 8entries returned from Tri-linear index address unit Resultant 8 bitstreated as fixed point 8:0 Transfer time is 8 entries at 1 byte perentry

Tri-linear interpolation returns interpolation between 8 values. Each 8bit value takes 1 cycle to be returned from the lookup, for a total of 8cycles. The tri-linear interpolation also takes 8 cycles when 2 MultiplyALUs are used per cycle. General tri-linear interpolation information isgiven in the ALU section of this document. The 512 bytes for the lookuptable fits in 16 cache lines.

The time taken to convert a single color component of image is therefore0.105 s (1500*1000*7 cycles*10 ns per cycle). To convert 3 componentstakes 0.415 s. Fortunately, the color space conversion for printouttakes place on the fly during printout itself, so is not a perceiveddelay.

If color components are converted separately, they must not overwritetheir input color space components since all color components from theinput color space are required for converting each component.

Since only 1 multiply unit is used to perform the interpolation, it isalternatively possible to do the entire Lab->CMY conversion as a singlepass. This would require 3 Vertical-Strip Read Iterators, 3Vertical-Strip Write Iterators, and access to 3 conversion tablessimultaneously. In that case, it is possible to write back onto theinput image and thus use no extra memory. However, access to 3conversion tables equals ⅓ of the caching for each, that could lead tohigh latency for the overall process.

Affine Transform

Prior to compositing an image with a photo, it may be necessary torotate, scale and translate it. If the image is only being translated,it can be faster to use a direct sub-pixel translation function.However, rotation, scale-up and translation can all be incorporated intoa single affine transform.

A general affine transform can be included as an accelerated function.Affine transforms are limited to 2D, and if scaling down, input imagesshould be pre-scaled via the Scale function. Having a general affinetransform function allows an output image to be constructed one block ata time, and can reduce the time taken to perform a number oftransformations on an image since all can be applied at the same time.

A transformation matrix needs to be supplied by the client—the matrixshould be the inverse matrix of the transformation desired i.e. applyingthe matrix to the output pixel coordinate will give the inputcoordinate.

A 2D matrix is usually represented as a 3×3 array:

$\quad\begin{bmatrix}a & b & 0 \\c & d & 0 \\e & f & 1\end{bmatrix}$

Since the 3^(rd) column is always [0, 0, 1] clients do not need tospecify it. Clients instead specify a, b, c, d, e, and f.

Given a coordinate in the output image (x, y) whose top left pixelcoordinate is given as (0, 0), the input coordinate is specified by:(ax+cy+e, bx+dy+f). Once the input coordinate is determined, the inputimage is sampled to arrive at the pixel value. Bi-linear interpolationof input image pixels is used to determine the value of the pixel at thecalculated coordinate. Since affine transforms preserve parallel lines,images are processed in output vertical strips of 32 pixels wide forbest average input image cache coherence.

Three Multiply ALUs are required to perform the bi-linear interpolationin 2 cycles. Multiply ALUs 1 and 2 do linear interpolation in X forlines Y and Y+1 respectively, and Multiply ALU 3 does linearinterpolation in Y between the values output by Multiply ALUs 1 and 2.

As we move to the right across an output line in X, 2 Adder ALUscalculate the actual input image coordinates by adding ‘a’ to thecurrent X value, and ‘b’ to the current Y value respectively. When weadvance to the next line (either the next line in a vertical strip afterprocessing a maximum of 32 pixels, or to the first line in a newvertical strip) we update X and Y to pre-calculated start coordinatevalues constants for the given block

The process for calculating an input coordinate is given in FIG. 96where the following constants are set by software:

Calculate Pixel

Once we have the input image coordinates, the input image must besampled. A lookup table is used to return the values at the specifiedcoordinates in readiness for bilinear interpolation. The basic processis as indicated in FIG. 97 and the following lookup table is used:

Lookup Size Details LU₁ Image Bilinear Image lookup [X, Y] width byTable indexed by the integer part of X and Y. Image 4 entries returnedfrom Bilinear index address unit, height 2 per cycle. 8 bits per Each 8bit entry treated as fixed point 8:0 entry Transfer time is 2 cycles (216 bit entries in FIFO hold the 4 8 bit entries)

The affine transform requires all 4 Multiply Units and all 4 Adder ALUs,and with good cache coherence can perform an affine transform with anaverage of 2 cycles per output pixel. This timing assumes good cachecoherence, which is true for non-skewed images. Worst case timings areseverely skewed images, which meaningful Vark scripts are unlikely tocontain.

The time taken to transform a 128×128 image is therefore 0.00033 seconds(32,768 cycles). If this is a clip image with 4 channels (including achannel), the total time taken is 0.00131 seconds (131,072 cycles).

A Vertical-Strip Write Iterator is required to output the pixels. NoRead Iterator is required. However, since the affine transformaccelerator is bound by time taken to access input image pixels, as manycache lines as possible should be allocated to the read of pixels fromthe input image. At least 32 should be available, and preferably 64 ormore.

Scaling

Scaling is essentially a re-sampling of an image. Scale up of an imagecan be performed using the Affine Transform function. Generalizedscaling of an image, including scale down, is performed by the hardwareaccelerated Scale function. Scaling is performed independently in X andY, so different scale factors can be used in each dimension.

The generalized scale unit must match the Affine Transform scalefunction in terms of registration. The generalized scaling process is asillustrated in FIG. 98. The scale in X is accomplished by Fant'sre-sampling algorithm as illustrated in FIG. 99.

Where the following constants are set by software:

Constant Value K₁ Number of input pixels that contribute to an outputpixel in X K₂ 1/K₁The following registers are used to hold temporary variables:

Variable Value Latch₁ Amount of input pixel remaining unused (starts at1 and decrements) Latch₂ Amount of input pixels remaining to contributeto current output pixel (starts at K₁ and decrements) Latch₃ Next pixel(in X) Latch₄ Current pixel Latch₅ Accumulator for output pixel(unscaled) Latch₆ Pixel Scaled in X (output)The Scale in Y process is illustrated in FIG. 100 and is alsoaccomplished by a slightly altered version of Fant's re-samplingalgorithm to account for processing in order of X pixels.Where the following constants are set by software:

Constant Value K₁ Number of input pixels that contribute to an outputpixel in Y K₂ 1/K₁The following registers are used to hold temporary variables:

Variable Value Latch₁ Amount of input pixel remaining unused (starts at1 and decrements) Latch₂ Amount of input pixels remaining to contributeto current output pixel (starts at K₁ and decrements) Latch₃ Next pixel(in Y) Latch₄ Current pixel Latch₅ Pixel Scaled in Y (output)The following DRAM FIFOs are used:

Lookup Size Details FIFO₁ ImageWidth_(OUT) entries 1 row of image pixelsalready scaled 8 bits per entry in X 1 cycle transfer time FIFO₂ImageWidth_(OUT) entries 1 row of image pixels already scaled 16 bitsper entry in X 2 cycles transfer time (1 byte per cycle)

Tessellate Image

Tessellation of an image is a form of tiling. It involves copying aspecially designed “tile” multiple times horizontally and verticallyinto a second (usually larger) image space. When tessellated, the smalltile forms a seamless picture. One example of this is a small tile of asection of a brick wall. It is designed so that when tessellated, itforms a full brick wall. Note that there is no scaling or sub-pixeltranslation involved in tessellation.

The most cache-coherent way to perform tessellation is to output theimage sequentially line by line, and to repeat the same line of theinput image for the duration of the line. When we finish the line, theinput image must also advance to the next line (and repeat it multipletimes across the output line).

An overview of the tessellation function is illustrated 390 in FIG. 101.The Sequential Read Iterator 392 is set up to continuously read a singleline of the input tile (StartLine would be 0 and EndLine would be 1).Each input pixel is written to all 3 of the Write Iterators 393-395. Acounter 397 in an Adder ALU counts down the number of pixels in anoutput line, terminating the sequence at the end of the line.

At the end of processing a line, a small software routine updates theSequential Read Iterator's StartLine and EndLine registers beforerestarting the microcode and the Sequential Read Iterator (which clearsthe FIFO and repeats line 2 of the tile). The Write Iterators 393-395are not updated, and simply keep on writing out to their respectiveparts of the output image. The net effect is that the tile has one linerepeated across an output line, and then the tile is repeated verticallytoo.

This process does not fully use the memory bandwidth since we get goodcache coherence in the input image, but it does allow the tessellationto function with tiles of any size. The process uses 1 Adder ALU. If the3 Write Iterators 393-395 each write to ⅓ of the image (breaking theimage on tile sized boundaries), then the entire tessellation processtakes place at an average speed of ⅓ cycle per output image pixel. Foran image of 1500×1000, this equates to 0.005 seconds (5,000,000 ns).

Sub-Pixel Translator

Before compositing an image with a background, it may be necessary totranslate it by a sub-pixel amount in both X and Y. Sub-pixel transformscan increase an image's size by 1 pixel in each dimension. The value ofthe region outside the image can be client determined, such as aconstant value (e.g. black), or edge pixel replication. Typically itwill be better to use black.

The sub-pixel translation process is as illustrated in FIG. 102.Sub-pixel translation in a given dimension is defined by:

Pixel_(out)=Pixel_(in)*(1−Translation)+Pixel_(in−1)*Translation

It can also be represented as a form of interpolation:

Pixel_(out)=Pixel_(in−)+(Pixel_(in)−Pixel_(in−1))*Translation

Implementation of a single (on average) cycle interpolation engine usinga single Multiply ALU and a single Adder ALU in conjunction isstraightforward. Sub-pixel translation in both X & Y requires 2interpolation engines.

In order to sub-pixel translate in Y, 2 Sequential Read Iterators 400,401 are required (one is reading a line ahead of the other from the sameimage), and a single Sequential Write Iterator 403 is required.

The first interpolation engine (interpolation in Y) accepts pairs ofdata from 2 streams, and linearly interpolates between them. The secondinterpolation engine (interpolation in X) accepts its data as a single 1dimensional stream and linearly interpolates between values. Bothengines interpolate in 1 cycle on average.

Each interpolation engine 405, 406 is capable of performing thesub-pixel translation in 1 cycle per output pixel on average. Theoverall time is therefore 1 cycle per output pixel, with requirements of2 Multiply ALUs and 2 Adder ALUs.

The time taken to output 32 pixels from the sub-pixel translate functionis on average 320 ns (32 cycles). This is enough time for 4 fullcache-line accesses to DRAM, so the use of 3 Sequential Iterators iswell within timing limits.

The total time taken to sub-pixel translate an image is therefore 1cycle per pixel of the output image. A typical image to be sub-pixeltranslated is a tile of size 128*128. The output image size is 129*129.The process takes 129*129*10 ns=166,410 ns.

The Image Tiler function also makes use of the sub-pixel translationalgorithm, but does not require the writing out of thesub-pixel-translated data, but rather processes it further.

Image Tiler

The high level algorithm for tiling an image is carried out in software.Once the placement of the tile has been determined, the appropriatecolored tile must be composited. The actual compositing of each tileonto an image is carried out in hardware via the microcoded ALUs.Compositing a tile involves both a texture application and a colorapplication to a background image. In some cases it is desirable tocompare the actual amount of texture added to the background in relationto the intended amount of texture, and use this to scale the color beingapplied. In these cases the texture must be applied first.

Since color application functionality and texture applicationfunctionality are somewhat independent, they are separated intosub-functions.

The number of cycles per 4-channel tile composite for the differenttexture styles and coloring styles is summarised in the following table:

Constant Pixel color color Replace texture 4 4.75 25% background + tiletexture 4 4.75 Average height algorithm 5 5.75 Average height algorithmwith feedback 5.75 6.5

Tile Coloring and Compositing

A tile is set to have either a constant color (for the whole tile), ortakes each pixel value from an input image. Both of these cases may alsohave feedback from a texturing stage to scale the opacity (similar tothinning paint).

The steps for the 4 cases can be summarised as:

-   -   Sub-pixel translate the tile's opacity values,    -   Optionally scale the tile's opacity (if feedback from texture        application is enabled).    -   Determine the color of the pixel (constant or from an image        map).    -   Composite the pixel onto the background image.

Each of the 4 cases is treated separately, in order to minimize the timetaken to perform the function. The summary of time per color compositingstyle for a single color channel is described in the following table:

No feedback Feedback from texture from texture Tiling color style(cycles per pixel) (cycles per pixel) Tile has constant color per pixel1 2 Tile has per pixel color from 1.25 2 input image

Constant Color

In this case, the tile has a constant color, determined by software.While the ACP 31 is placing down one tile, the software can bedetermining the placement and coloring of the next tile.

The color of the tile can be determined by bi-linear interpolation intoa scaled version of the image being tiled. The scaled version of theimage can be created and stored in place of the image pyramid, and needsonly to be performed once per entire tile operation. If the tile size is128×128, then the image can be scaled down by 128:1 in each dimension.

Without Feedback

When there is no feedback from the texturing of a tile, the tile issimply placed at the specified coordinates. The tile color is used foreach pixel's color, and the opacity for the composite comes from thetile's sub-pixel translated opacity channel. In this case color channelsand the texture channel can be processed completely independentlybetween tiling passes.

The overview of the process is illustrated in FIG. 103. Sub-pixeltranslation 410 of a tile can be accomplished using 2 Multiply ALUs and2 Adder ALUs in an average time of 1 cycle per output pixel. The outputfrom the sub-pixel translation is the mask to be used in compositing 411the constant tile color 412 with the background image from backgroundsequential Read Iterator.

Compositing can be performed using 1 Multiply ALU and 1 Adder ALU in anaverage time of 1 cycle per composite. Requirements are therefore 3Multiply ALUs and 3 Adder ALUs. 4 Sequential Iterators 413-416 arerequired, taking 320 ns to read or write their contents. With an averagenumber of cycles of 1 per pixel to sub-pixel translate and composite,there is sufficient time to read and write the buffers.

With Feedback

When there is feedback from the texturing of a tile, the tile is placedat the specified coordinates. The tile color is used for each pixel'scolor, and the opacity for the composite comes from the tile's sub-pixeltranslated opacity channel scaled by the feedback parameter. Thus thetexture values must be calculated before the color value is applied.

The overview of the process is illustrated in FIG. 97. Sub-pixeltranslation of a tile can be accomplished using 2 Multiply ALUs and 2Adder ALUs in an average time of 1 cycle per output pixel. The outputfrom the sub-pixel translation is the mask to be scaled according to thefeedback read from the Feedback Sequential Read Iterator 420. Thefeedback is passed it to a Scaler (1 Multiply ALU) 421.

Compositing 422 can be performed using 1 Multiply ALU and 1 Adder ALU inan average time of 1 cycle per composite. Requirements are therefore 4Multiply ALUs and all 4 Adder ALUs. Although the entire process can beaccomplished in 1 cycle on average, the bottleneck is the memory access,since 5 Sequential Iterators are required. With sufficient buffering,the average time is 1.25 cycles per pixel.

Color from Input Image

One way of coloring pixels in a tile is to take the color from pixels inan input image. Again, there are two possibilities for compositing: withand without feedback from the texturing.

Without Feedback

In this case, the tile color simply comes from the relative pixel in theinput image. The opacity for compositing comes from the tile's opacitychannel sub-pixel shifted.

The overview of the process is illustrated in FIG. 105. Sub-pixeltranslation 425 of a tile can be accomplished using 2 Multiply ALUs and2 Adder ALUs in an average time of 1 cycle per output pixel. The outputfrom the sub-pixel translation is the mask to be used in compositing 426the tile's pixel color (read from the input image 428) with thebackground image 429.

Compositing 426 can be performed using 1 Multiply ALU and 1 Adder ALU inan average time of 1 cycle per composite. Requirements are therefore 3Multiply ALUs and 3 Adder ALUs. Although the entire process can beaccomplished in 1 cycle on average, the bottleneck is the memory access,since 5 Sequential Iterators are required. With sufficient buffering,the average time is 1.25 cycles per pixel.

With Feedback

In this case, the tile color still comes from the relative pixel in theinput image, but the opacity for compositing is affected by the relativeamount of texture height actually applied during the texturing pass.This process is as illustrated in FIG. 106.

Sub-pixel translation 431 of a tile can be accomplished using 2 MultiplyALUs and 2 Adder ALUs in an average time of 1 cycle per output pixel.The output from the sub-pixel translation is the mask to be scaled 431according to the feedback read from the Feedback Sequential ReadIterator 432. The feedback is passed to a Scaler (1 Multiply ALU) 431.Compositing 434 can be performed using 1 Multiply ALU and 1 Adder ALU inan average time of 1 cycle per composite.

Requirements are therefore all 4 Multiply ALUs and 3 Adder ALUs.Although the entire process can be accomplished in 1 cycle on average,the bottleneck is the memory access, since 6 Sequential Iterators arerequired. With sufficient buffering, the average time is 1.5 cycles perpixel.

Tile Texturing

Each tile has a surface texture defined by its texture channel. Thetexture must be sub-pixel translated and then applied to the outputimage. There are 3 styles of texture compositing:

-   -   Replace texture    -   25% background+tile's texture    -   Average height algorithm

In addition, the Average height algorithm can save feedback parametersfor color compositing.

The time taken per texture compositing style is summarised in thefollowing table:

Cycles per pixel Cycles per pixel (no feedback from (feedback fromTiling color style texture) texture) Replace texture 1 — 25%background + tile 1 — texture value Average height algorithm 2 2

Replace Texture

In this instance, the texture from the tile replaces the texture channelof the image, as illustrated in FIG. 107. Sub-pixel translation 436 of atile's texture can be accomplished using 2 Multiply ALUs and 2 AdderALUs in an average time of 1 cycle per output pixel. The output fromthis sub-pixel translation is fed directly to the Sequential WriteIterator 437.

The time taken for replace texture compositing is 1 cycle per pixel.There is no feedback, since 100% of the texture value is always appliedto the background. There is therefore no requirement for processing thechannels in any particular order.

25% Background+Tile's Texture

In this instance, the texture from the tile is added to 25% of theexisting texture value. The new value must be greater than or equal tothe original value. In addition, the new texture value must be clippedat 255 since the texture channel is only 8 bits. The process utilised isillustrated in FIG. 108.

Sub-pixel translation 440 of a tile's texture can be accomplished using2 Multiply ALUs and 2 Adder ALUs in an average time of 1 cycle peroutput pixel. The output from this sub-pixel translation 440 is fed toan adder 441 where it is added to ¼ 442 of the background texture value.Min and Max functions 444 are provided by the 2 adders not used forsub-pixel translation and the output written to a Sequential WriteIterator 445.

The time taken for this style of texture compositing is 1 cycle perpixel. There is no feedback, since 100% of the texture value isconsidered to have been applied to the background (even if clipping at255 occurred). There is therefore no requirement for processing thechannels in any particular order.

Average Height Algorithm

In this texture application algorithm, the average height under the tileis computed, and each pixel's height is compared to the average height.If the pixel's height is less than the average, the stroke height isadded to the background height. If the pixel's height is greater than orequal to the average, then the stroke height is added to the averageheight. Thus background peaks thin the stroke. The height is constrainedto increase by a minimum amount to prevent the background from thinningthe stroke application to 0 (the minimum amount can be 0 however). Theheight is also clipped at 255 due to the 8-bit resolution of the texturechannel.

There can be feedback of the difference in texture applied versus theexpected amount applied. The feedback amount can be used as a scalefactor in the application of the tile's color.

In both cases, the average texture is provided by software, calculatedby performing a bi-level interpolation on a scaled version of thetexture map. Software determines the next tile's average texture heightwhile the current tile is being applied. Software must also provide theminimum thickness for addition, which is typically constant for theentire tiling process.

Without Feedback

With no feedback, the texture is simply applied to the backgroundtexture, as shown in FIG. 109.

4 Sequential Iterators are required, which means that if the process canbe pipelined for 1 cycle, the memory is fast enough to keep up.

Sub-pixel translation 450 of a tile's texture can be accomplished using2 Multiply ALUs and 2 Adder ALUs in an average time of 1 cycle peroutput pixel. Each Min & Max function 451,452 requires a separate AdderALU in order to complete the entire operation in 1 cycle. Since 2 arealready used by the sub-pixel translation of the texture, there are notenough remaining for a 1 cycle average time.

The average time for processing 1 pixel's texture is therefore 2 cycles.Note that there is no feedback, and hence the color channel order ofcompositing is irrelevant.

With Feedback

This is conceptually the same as the case without feedback, except thatin addition to the standard processing of the texture applicationalgorithm, it is necessary to also record the proportion of the textureactually applied. The proportion can be used as a scale factor forsubsequent compositing of the tile's color onto the background image. Aflow diagram is illustrated in FIG. 110 and the following lookup tableis used:

Lookup Size Details LU₁ 256 entries 1/N 16 bits per entry Table indexedby N (range 0-255) Resultant 16 bits treated as fixed point 0:16

Each of the 256 entries in the software provided 1/N table 460 is 16bits, thus requiring 16 cache lines to hold continuously.

Sub-pixel translation 461 of a tile's texture can be accomplished using2 Multiply ALUs and 2 Adder ALUs in an average time of 1 cycle peroutput pixel. Each Min 462 & Max 463 function requires a separate AdderALU in order to complete the entire operation in 1 cycle. Since 2 arealready used by the sub-pixel translation of the texture, there are notenough remaining for a 1 cycle average time.

The average time for processing 1 pixel's texture is therefore 2 cycles.Sufficient space must be allocated for the feedback data area (a tilesized image channel). The texture must be applied before the tile'scolor is applied, since the feedback is used in scaling the tile'sopacity.

CCD Image Interpolator

Images obtained from the CCD via the ISI 83 (FIG. 3) are 750×500 pixels.When the image is captured via the ISI, the orientation of the camera isused to rotate the pixels by 0, 90, 180, or 270 degrees so that the topof the image corresponds to ‘up’. Since every pixel only has an R, G, orB color component (rather than all 3), the fact that these have beenrotated must be taken into account when interpreting the pixel values.Depending on the orientation of the camera, each 2×2 pixel block has oneof the configurations illustrated in FIG. 111:

Several processes need to be performed on the CCD captured image inorder to transform it into a useful form for processing:

-   -   Up-interpolation of low-sample rate color components in CCD        image (interpreting correct orientation of pixels)        Color Conversion from RGB to the Internal Color Space    -   Scaling of the internal space image from 750×500 to 1500×1000.    -   Writing out the image in a planar format

The entire channel of an image is required to be available at the sametime in order to allow warping. In a low memory model (8 MB), there isonly enough space to hold a single channel at full resolution as atemporary object. Thus the color conversion is to a single colorchannel. The limiting factor on the process is the color conversion, asit involves tri-linear interpolation from RGB to the internal colorspace, a process that takes 0.026 ns per channel (750×500×7 cycles perpixel×10 ns per cycle=26,250,000 ns).

It is important to perform the color conversion before scaling of theinternal color space image as this reduces the number of pixels scaled(and hence the overall process time) by a factor of 4.

The requirements for all of the transformations may not fit in the ALUscheme. The transformations are therefore broken into two phases:

Phase 1: Up-Interpolation of Low-Sample Rate Color Components in CCDImage (Interpreting Correct Orientation of Pixels)

Color conversion from RGB to the internal color space Writing out theimage in a planar format

Phase 2: Scaling of the Internal Space Image from 750×500 to 1500×1000

Separating out the scale function implies that the small color convertedimage must be in memory at the same time as the large one. The outputfrom Phase 1 (0.5 MB) can be safely written to the memory area usuallykept for the image pyramid (1 MB). The output from Phase 2 can be thegeneral expanded CCD image. Separation of the scaling also allows thescaling to be accomplished by the Affine Transform, and also allows fora different CCD resolution that may not be a simple 1:2 expansion.

Phase 1: Up-Interpolation of Low-Sample Rate Color Components.

Each of the 3 color components (R, G, and B) needs to be up interpolatedin order for color conversion to take place for a given pixel. We have 7cycles to perform the interpolation per pixel since the color conversiontakes 7 cycles.

Interpolation of G is straightforward and is illustrated in FIG. 112.Depending on orientation, the actual pixel value G alternates betweenodd pixels on odd lines & even pixels on even lines, and odd pixels oneven lines & even pixels on odd lines. In both cases, linearinterpolation is all that is required. Interpolation of R and Bcomponents as illustrated in FIG. 113 and FIG. 113, is more complicated,since in the horizontal and vertical directions, as can be seen from thediagrams, access to 3 rows of pixels simultaneously is required, so 3Sequential Read Iterators are required, each one offset by a single row.In addition, we have access to the previous pixel on the same row via alatch for each row.

Each pixel therefore contains one component from the CCD, and the other2 up-interpolated. When one component is being bi-linearly interpolated,the other is being linearly interpolated. Since the interpolation factoris a constant 0.5, interpolation can be calculated by an add and a shift1 bit right (in 1 cycle), and bi-linear interpolation of factor 0.5 canbe calculated by 3 adds and a shift 2 bits right (3 cycles). The totalnumber of cycles required is therefore 4, using a single multiply ALU.

FIG. 115 illustrates the case for rotation 0 even line even pixel (EL,EP), and odd line odd pixel (OL, OP) and FIG. 116 illustrates the casefor rotation 0 even line odd pixel (EL, OP), and odd line even pixel(OL, EP). The other rotations are simply different forms of these twoexpressions.

Color Conversion

Color space conversion from RGB to Lab is achieved using the same methodas that described in the general Color Space Convert function, a processthat takes 8 cycles per pixel. Phase 1 processing can be described withreference to FIG. 117.

The up-interpolate of the RGB takes 4 cycles (1 Multiply ALU), but theconversion of the color space takes 8 cycles per pixel (2 Multiply ALUs)due to the lookup transfer time.

Phase 2

Scaling the Image

This phase is concerned with up-interpolating the image from the CCDresolution (750×500) to the working photo resolution (1500×1000).Scaling is accomplished by running the Affine transform with a scale of1:2. The timing of a general affine transform is 2 cycles per outputpixel, which in this case means an elapsed scaling time of 0.03 seconds.

Illuminate Image

Once an image has been processed, it can be illuminated by one or morelight sources. Light sources can be:

1. Directional—is infinitely distant so it casts parallel light in asingle direction

2. Omni—casts unfocused lights in all directions.

3. Spot—casts a focused beam of light at a specific target point. Thereis a cone and penumbra associated with a spotlight.

The scene may also have an associated bump-map to cause reflectionangles to vary. Ambient light is also optionally present in anilluminated scene.

In the process of accelerated illumination, we are concerned withilluminating one image channel by a single light source. Multiple lightsources can be applied to a single image channel as multiple passes onepass per light source. Multiple channels can be processed one at a timewith or without a bump-map.

The normal surface vector (N) at a pixel is computed from the bump-mapif present. The default normal vector, in the absence of a bump-map, isperpendicular to the image plane i.e. N=[0, 0, 1].

The viewing vector V is always perpendicular to the image plane i.e.V=[0, 0, 1].

For a directional light source, the light source vector (L) from a pixelto the light source is constant across the entire image, so is computedonce for the entire image. For an omni light source (at a finitedistance), the light source vector is computed independently for eachpixel.

A pixel's reflection of ambient light is computed according to:I_(a)k_(a)O_(d)

A pixel's diffuse and specular reflection of a light source is computedaccording to the Phong model:

f_(att)I_(p)[k_(d)O_(d)(N·L)+k_(s)O_(s)(R·V)^(n)]

When the light source is at infinity, the light source intensity isconstant across the image.

Each light source has three contributions per pixel

-   -   Ambient Contribution    -   Diffuse contribution    -   Specular contribution

The light source can be defined using the following variables:

d_(L) Distance from light source f_(att) Attenuation with distance[f_(att) = 1/d_(L) ²] R Normalised reflection vector [R = 2N(N · L ) −L] I_(a) Ambient light intensity I_(p) Diffuse light coefficient k_(a)Ambient reflection coefficient k_(d) Diffuse reflection coefficientk_(s) Specular reflection coefficient k_(sc) Specular color coefficientL Normalised light source vector N Normalised surface normal vector nSpecular exponent O_(d) Object's diffuse color (i.e. image pixel color)O_(s) Object's specular color (k_(sc)O_(d) + (1 − k_(sc))I_(p)) VNormalised viewing vector [V = [0, 0, 1]]The same reflection coefficients (k_(a), k_(s), k_(d)) are used for eachcolor component.

A given pixel's value will be equal to the ambient contribution plus thesum of each light's diffuse and specular contribution.

Sub-Processes of Illumination Calculation

In order to calculate diffuse and specular contributions, a variety ofother calculations are required. These are calculations of:

1/√X

N

L

N·L

R·V

f_(att)

f_(cp)

Sub-processes are also defined for calculating the contributions of:

ambient

diffuse

specular

The sub-processes can then be used to calculate the overall illuminationof a light source. Since there are only 4 multiply ALUs, the microcodefor a particular type of light source can have sub-processesintermingled appropriately for performance.

Calculation of 1/√X

The Vark lighting model uses vectors. In many cases it is important tocalculate the inverse of the length of the vector for normalizationpurposes. Calculating the inverse of the length requires the calculationof 1/SquareRoot[X].

Logically, the process can be represented as a process with inputs andoutputs as shown in FIG. 118. Referring to FIG. 119, the calculation canbe made via a lookup of the estimation, followed by a single iterationof the following function:

V _(n+1)=½V _(n)(3−XV _(n) ²)

The number of iterations depends on the accuracy required. In this caseonly 16 bits of precision are required. The table can therefore have 8bits of precision, and only a single iteration is necessary. Thefollowing constant is set by software:

Constant Value K₁ 3The following lookup table is used:

Lookup Size Details LU₁ 256 entries 1/SquareRoot[X] 8 bits per entryTable indexed by the 8 highest significant bits of X. Resultant 8 bitstreated as fixed point 0:8

Calculation of N

N is the surface normal vector. When there is no bump-map, N isconstant. When a bump-map is present, N must be calculated for eachpixel.

No Bump-Map

When there is no bump-map, there is a fixed normal N that has thefollowing properties:

N=[X_(N), Y_(N), Z_(N)]=[0, 0, 1] ∥N∥=1 1/∥N∥=1

normalized N=N

These properties can be used instead of specifically calculating thenormal vector and 1/∥N∥ and thus optimize other calculations.

With Bump-Map

As illustrated in FIG. 120, when a bump-map is present, N is calculatedby comparing bump-map values in X and Y dimensions. FIG. 120 shows thecalculation of N for pixel P1 in terms of the pixels in the same row andcolumn, but not including the value at P1 itself. The calculation of Nis made resolution independent by multiplying by a scale factor (samescale factor in X & Y). This process can be represented as a processhaving inputs and outputs (Z_(N) is always 1) as illustrated in FIG.121.

As Z_(N) is always 1. Consequently X_(N) and Y_(N) are not normalizedyet (since Z_(N)=1). Normalization of N is delayed until aftercalculation of N·L so that there is only 1 multiply by 1/∥N∥ instead of3.

An actual process for calculating N is illustrated in FIG. 122.

The following constant is set by software:

Constant Value K₁ ScaleFactor (to make N resolution independent)

Calculation of L Directional Lights

When a light source is infinitely distant, it has an effective constantlight vector L. L is normalized and calculated by software such that:

L=[X_(L), Y_(L), Z_(L)]

∥L∥=1

1/∥L∥=1

These properties can be used instead of specifically calculating the Land 1/∥L∥ and thus optimize other calculations. This process is asillustrated in FIG. 123.

Omni Lights and Spotlights

When the light source is not infinitely distant, L is the vector fromthe current point P to the light source PL. Since P=[X_(P), Y_(P), 0], Lis given by:

L=[X_(L), Y_(L), Z_(L)]

X_(L)=X_(P)−X_(PL)

Y_(L)=Y_(P)−Y_(PL)

Z_(L)=−Z_(PL)

We normalize X_(L), Y_(L) and Z_(L) by multiplying each by 1/∥L∥. Thecalculation of 1/∥L∥ (for later use in normalizing) is accomplished bycalculating

V=X _(L) ² +Y _(L) ² +Z _(L) ²

and then calculating V^(−1/2)

In this case, the calculation of L can be represented as a process withthe inputs and outputs as indicated in FIG. 124.

X_(P) and Y_(P) are the coordinates of the pixel whose illumination isbeing calculated. Z_(P) is always 0.

The actual process for calculating L can be as set out in FIG. 125.

Where the following constants are set by software:

Constant Value K₁ X_(PL) K₂ Y_(PL) K₃ Z_(PL) ² (as Z_(P) is 0) K₄−Z_(PL)

Calculation of N·L

Calculating the dot product of vectors N and L is defined as:

X_(N)X_(L)+Y_(N)Y_(L)+Z_(N)Z_(L) No Bump-Map

When there is no bump-map N is a constant [0, 0, 1]. N·L thereforereduces to Z_(L).

With Bump-Map

When there is a bump-map, we must calculate the dot product directly.Rather than take in normalized N components, we normalize after takingthe dot product of a non-normalized N to a normalized L. L is eithernormalized by software (if it is constant), or by the Calculate Lprocess. This process is as illustrated in FIG. 126.

Note that Z_(N) is not required as input since it is defined to be 1.However 1/∥N∥ is required instead, in order to normalize the result. Oneactual process for calculating N·L is as illustrated in FIG. 127.

Calculation of R·V

R·V is required as input to specular contribution calculations. SinceV=[0, 0, 1], only the Z components are required. R·V therefore reducesto:

R·V=2Z _(N)(N·L)−Z _(L)

In addition, since the un-normalized Z_(N)=1, normalized Z_(N)=1/∥N∥

No Bump-Map

The simplest implementation is when N is constant (i.e. no bump-map).Since N and V are constant, N·L and R·V can be simplified:

V = [0, 0, 1] N = [0, 0, 1] L = [X_(L), Y_(L), Z_(L)] N.L = Z_(L)$\begin{matrix}{{R\; \bullet \; V} = {{2{Z_{N}\left( {N.L} \right)}} - Z_{L}}} \\{= {{2Z_{L}} - Z_{L}}} \\{= Z_{L}}\end{matrix}$

When L is constant (Directional light source), a normalized Z_(L) can besupplied by software in the form of a constant whenever R·V is required.When L varies (Omni lights and Spotlights), normalized Z_(L) must becalculated on the fly. It is obtained as output from the Calculate Lprocess.

With Bump-Map

When N is not constant, the process of calculating R·V is simply animplementation of the generalized formula:

R·V=2Z _(N)(N·L)−Z _(L)

The inputs and outputs are as shown in FIG. 128 with the an actualimplementation as shown in FIG. 129.

Calculation of Attenuation Factor Directional Lights

When a light source is infinitely distant, the intensity of the lightdoes not vary across the image. The attenuation factor f_(att) istherefore 1. This constant can be used to optimize illuminationcalculations for infinitely distant light sources.

Omni Lights and Spotlights

When a light source is not infinitely distant, the intensity of thelight can vary according to the following formula:

f _(att) =f ₀ f ₁ /d+f ₂ /d ²

Appropriate settings of coefficients f₀, f₁, and f₂ allow lightintensity to be attenuated by a constant, linearly with distance, or bythe square of the distance.

Since d=∥L∥, the calculation of f_(att) can be represented as a processwith the following inputs and outputs as illustrated in FIG. 130.

The actual process for calculating f_(att) can be defined in FIG. 131.

Where the following constants are set by software:

Constant Value K₁ F₂ K₂ f₁ K₃ F₀

Calculation of Cone and Penumbra Factor Directional Lights and OmniLights

These two light sources are not focused, and therefore have no cone orpenumbra. The cone-penumbra scaling factor f_(cp) is therefore 1. Thisconstant can be used to optimize illumination calculations forDirectional and Omni light sources.

Spotlights

A spotlight focuses on a particular target point (PT). The intensity ofthe Spotlight varies according to whether the particular point of theimage is in the cone, in the penumbra, or outside the cone/penumbraregion.

Turning now to FIG. 132, there is illustrated a graph of f_(cp) withrespect to the penumbra position. Inside the cone 470, f_(cp) is 1,outside 471 the penumbra f_(cp) is 0. From the edge of the cone throughto the end of the penumbra, the light intensity varies according to acubic function 472.

The various vectors for penumbra 475 and cone 476 calculation are asillustrated in FIG. 133 and FIG. 134.

Looking at the surface of the image in 1 dimension as shown in FIG. 134,3 angles A, B, and C are defined. A is the angle between the targetpoint 479, the light source 478, and the end of the cone 480. C is theangle between the target point 479, light source 478, and the end of thepenumbra 481. Both are fixed for a given light source. B is the anglebetween the target point 479, the light source 478, and the positionbeing calculated 482, and therefore changes with every point beingcalculated on the image.

We normalize the range A to C to be 0 to 1, and find the distance that Bis along that angle range by the formula:

(B−A)/(C−A)

The range is forced to be in the range 0 to 1 by truncation, and thisvalue used as a lookup for the cubic approximation of f_(cp).

The calculation of f_(att) can therefore be represented as a processwith the inputs and outputs as illustrated in FIG. 135 with an actualprocess for calculating f_(cp) is as shown in FIG. 136 where thefollowing constants are set by software:

Constant Value K₁ X_(LT) K₂ Y_(LT) K₃ Z_(LT) K₄ A K₅ 1/(C − A). [MAXNUMif no penumbra]The following lookup tables are used:

Lookup Size Details LU₁ 64 entries Arcos(X) 16 bits per entry Units aresame as for constants K₅ and K₆ Table indexed by highest 6 bits Resultby linear interpolation of 2 entries Timing is 2 * 8 bits * 2 entries =4 cycles LU₂ 64 entries Light Response function f_(cp) 16 bits per entryF(1) = 0, F(0) = 1, others are according to cubic Table indexed by 6bits (1:5) Result by linear interpolation of 2 entries Timing is 2 * 8bits = 4 cycles

Calculation of Ambient Contribution

Regardless of the number of lights being applied to an image, theambient light contribution is performed once for each pixel, and doesnot depend on the bump-map.

The ambient calculation process can be represented as a process with theinputs and outputs as illustrated in FIG. 131. The implementation of theprocess requires multiplying each pixel from the input image (O_(d)) bya constant value (I_(a)k_(a)), as shown in FIG. 138 where the followingconstant is set by software:

Constant Value K₁ I_(a)k_(a)

Calculation of Diffuse Contribution

Each light that is applied to a surface produces a diffuse illumination.The diffuse illumination is given by the formula:

diffuse=k _(d) O _(d)(N·L)

There are 2 different implementations to consider:

Implementation 1—Constant N and L

When N and L are both constant (Directional light and no bump-map):

N·L=Z _(L)

Therefore:

diffuse=k _(d) O _(d) Z _(L)

Since O_(d) is the only variable, the actual process for calculating thediffuse contribution is as illustrated in FIG. 139 where the followingconstant is set by software:

Constant Value K₁ k_(d)(N · L ) = k_(d)Z_(L)

Implementation 2—Non-Constant N & L

When either N or L are non-constant (either a bump-map or illuminationfrom an Omni light or a Spotlight), the diffuse calculation is performeddirectly according to the formula:

diffuse=k _(d) O _(d)(N·L)

The diffuse calculation process can be represented as a process with theinputs as illustrated in FIG. 140. N·L can either be calculated usingthe Calculate N·L Process, or is provided as a constant. An actualprocess for calculating the diffuse contribution is as shown in FIG. 141where the following constants are set by software:

Constant Value K₁ k_(d)

Calculation of Specular Contribution

Each light that is applied to a surface produces a specularillumination. The specular illumination is given by the formula:

specular=k ₅ O ₅(R·V)^(n)

where O_(s)=k_(sc)O_(d)+(1−k_(sc))I_(p)

There are two implementations of the Calculate Specular process.

Implementation 1—Constant N and L

The first implementation is when both N and L are constant (Directionallight and no bump-map). Since N, L and V are constant, N·L and R·V arealso constant:

V = [0, 0, 1] N = [0, 0, 1] L = [X_(L), Y_(L), Z_(L)] N.L = Z_(L)$\begin{matrix}{{R\; \bullet \; V} = {{2{Z_{N}\left( {N.L} \right)}} - Z_{L}}} \\{= {{2Z_{L}} - Z_{L}}} \\{= Z_{L}}\end{matrix}$

The specular calculation can thus be reduced to:

$\begin{matrix}{{specular} = {k_{s}O_{s}Z_{L}^{n}}} \\{= {k_{s}{Z_{L}^{n}\left( {{k_{sc}O_{d}} + {\left( {1 - k_{sc}} \right)I_{p}}} \right)}}} \\{= {{k_{s}k_{sc}Z_{L}^{n}O_{d}} + {\left( {1 - k_{sc}} \right)I_{p}k_{s}Z_{L}^{n}}}}\end{matrix}$

Since only O_(d) is a variable in the specular calculation, thecalculation of the specular contribution can therefore be represented asa process with the inputs and outputs as indicated in FIG. 142 and anactual process for calculating the specular contribution is illustratedin FIG. 143 where the following constants are set by software:

Constant Value K₁ k_(s)k_(sc)Z_(L) ^(n) K₂ (1 − k_(sc))I_(p)k_(s)Z_(L)^(n)

Implementation 2—Non Constant N and L

This implementation is when either N or L are not constant (either abump-map or illumination from an Omni light or a Spotlight). Thisimplies that R·V must be supplied, and hence R·V^(n) must also becalculated.

The specular calculation process can be represented as a process withthe inputs and outputs as shown in FIG. 144. FIG. 145 shows an actualprocess for calculating the specular contribution where the followingconstants are set by software:

Constant Value K₁ k_(s) K₂ k_(sc) K₃ (1 − k_(sc))I_(p)The following lookup table is used:

Lookup Size Details LU₁ 32 entries X^(n) 16 bits per Table indexed by 5highest bits of integer R · V entry Result by linear interpolation of 2entries using fraction of R · V. Interpolation by 2 Multiplies. The timetaken to retrieve the data from the lookup is 2 * 8 bits * 2 entries = 4cycles.

When Ambient Light is the Only Illumination

If the ambient contribution is the only light source, the process isvery straightforward since it is not necessary to add the ambient lightto anything with the overall process being as illustrated in FIG. 146.We can divide the image vertically into 2 sections, and process eachhalf simultaneously by duplicating the ambient light logic (thus using atotal of 2 Multiply ALUs and 4 Sequential Iterators). The timing istherefore ½ cycle per pixel for ambient light application.

The typical illumination case is a scene lit by one or more lights. Inthese cases, because ambient light calculation is so cheap, the ambientcalculation is included with the processing of each light source. Thefirst light to be processed should have the correct I_(a)k_(a) setting,and subsequent lights should have an I_(a)k_(a) value of 0 (to preventmultiple ambient contributions).

If the ambient light is processed as a separate pass (and not the firstpass), it is necessary to add the ambient light to the currentcalculated value (requiring a read and write to the same address). Theprocess overview is shown in FIG. 147.

The process uses 3 Image Iterators, 1 Multiply ALU, and takes 1 cycleper pixel on average.

Infinite Light Source

In the case of the infinite light source, we have a constant lightsource intensity across the image. Thus both L and f_(att) are constant.

No Bump Map

When there is no bump-map, there is a constant normal vector N [0, 0,1]. The complexity of the illumination is greatly reduced by theconstants of N, L, and f_(att). The process of applying a singleDirectional light with no bump-map is as illustrated in FIG. 147 wherethe following constant is set by software:

Constant Value K₁ I_(p)

For a single infinite light source we want to perform the logicaloperations as shown in FIG. 148 where K₁ through K₄ are constants withthe following values:

Constant Value K₁ K_(d)(NsL) = K_(d) L_(Z) K₂ k_(sc) K₃ K_(s)(NsH)^(n) =K_(s) H_(Z) ² K₄ I_(p)

The process can be simplified since K₂, K₃, and K₄ are constants. Sincethe complexity is essentially in the calculation of the specular anddiffuse contributions (using 3 of the Multiply ALUs), it is possible tosafely add an ambient calculation as the 4^(th) Multiply ALU. The firstinfinite light source being processed can have the true ambient lightparameter I_(a)k_(a), and all subsequent infinite lights can setI_(a)k_(a) to be 0. The ambient light calculation becomes effectivelyfree.

If the infinite light source is the first light being applied, there isno need to include the existing contributions made by other lightsources and the situation is as illustrated in FIG. 149 where theconstants have the following values:

Constant Value K₁ k_(d)(LsN) = k_(d)L_(Z) K₄ I_(p) K₅ (1 −k_(s)(NsH)^(n))I_(p) = (1 − k_(s)H_(Z) ^(n))I_(p) K₆k_(sc)k_(s)(NsH)^(n) I_(p) = k_(sc)k_(s)H_(Z) ^(n)I_(p) K₇ I_(a)k_(a)

If the infinite light source is not the first light being applied, theexisting contribution made by previously processed lights must beincluded (the same constants apply) and the situation is as illustratedin FIG. 148.

In the first case 2 Sequential Iterators 490, 491 are required, and inthe second case, 3 Sequential Iterators 490, 491, 492 (the extraIterator is required to read the previous light contributions). In bothcases, the application of an infinite light source with no bump maptakes 1 cycle per pixel, including optional application of the ambientlight.

With Bump Map

When there is a bump-map, the normal vector N must be calculated perpixel and applied to the constant light source vector L. 1/∥N∥ is alsoused to calculate R·V, which is required as input to the CalculateSpecular 2 process. The following constants are set by software:

Constant Value K₁ X_(L) K₂ Y_(L) K₃ Z_(L) K₄ I_(p)

Bump-map Sequential Read Iterator 490 is responsible for reading thecurrent line of the bump-map. It provides the input for determining theslope in X. Bump-map Sequential Read Iterators 491, 492 and areresponsible for reading the line above and below the current line. Theyprovide the input for determining the slope in Y.

Omni Lights

In the case of the Omni light source, the lighting vector L andattenuation factor f_(att) change for each pixel across an image.Therefore both L and f_(att) must be calculated for each pixel.

No Bump Map

When there is no bump-map, there is a constant normal vector N [0, 0,1]. Although L must be calculated for each pixel, both N·L and R·V aresimplified to Z_(L). When there is no bump-map, the application of anOmni light can be calculated as shown in FIG. 149 where the followingconstants are set by software:

Constant Value K₁ X_(P) K₂ Y_(P) K₃ I_(p)

The algorithm optionally includes the contributions from previous lightsources, and also includes an ambient light calculation. Ambient lightneeds only to be included once. For all other light passes, theappropriate constant in the Calculate Ambient process should be set to0.

The algorithm as shown requires a total of 19 multiply/accumulates. Thetimes taken for the lookups are 1 cycle during the calculation of L, and4 cycles during the specular contribution. The processing time of 5cycles is therefore the best that can be accomplished. The time taken isincreased to 6 cycles in case it is not possible to optimally microcodethe ALUs for the function. The speed for applying an Omni light onto animage with no associated bump-map is 6 cycles per pixel.

With Bump-Map

When an Omni light is applied to an image with an associated a bump-map,calculation of N, L, N·L and R·V are all necessary. The process ofapplying an Omni light onto an image with an associated bump-map is asindicated in FIG. 150 where the following constants are set by software:

Constant Value K₁ X_(P) K₂ Y_(P) K₃ I_(p)

The algorithm optionally includes the contributions from previous lightsources, and also includes an ambient light calculation. Ambient lightneeds only to be included once. For all other light passes, theappropriate constant in the Calculate Ambient process should be set to0.

The algorithm as shown requires a total of 32 multiply/accumulates. Thetimes taken for the lookups are 1 cycle each during the calculation ofboth L and N, and 4 cycles for the specular contribution. However thelookup required for N and L are both the same (thus 2 LUs implement the3 LUs). The processing time of 8 cycles is adequate. The time taken isextended to 9 cycles in case it is not possible to optimally microcodethe ALUs for the function. The speed for applying an Omni light onto animage with an associated bump-map is 9 cycles per pixel.

Spotlights

Spotlights are similar to Omni lights except that the attenuation factorf_(att) is modified by a cone/penumbra factor f_(cp) that effectivelyfocuses the light around a target.

No Bump-Map

When there is no bump-map, there is a constant normal vector N [0, 0,1]. Although L must be calculated for each pixel, both N·L and R·V aresimplified to Z_(L). FIG. 151 illustrates the application of a Spotlightto an image where the following constants are set by software:

Constant Value K₁ X_(P) K₂ Y_(P) K₃ I_(p)

The algorithm optionally includes the contributions from previous lightsources, and also includes an ambient light calculation. Ambient lightneeds only to be included once. For all other light passes, theappropriate constant in the Calculate Ambient process should be set to0.

The algorithm as shown requires a total of 30 multiply/accumulates. Thetimes taken for the lookups are 1 cycle during the calculation of L, 4cycles for the specular contribution, and 2 sets of 4 cycle lookups inthe cone/penumbra calculation.

With Bump-Map

When a Spotlight is applied to an image with an associated a bump-map,calculation of N, L, N·L and R·V are all necessary. The process ofapplying a single Spotlight onto an image with associated bump-map isillustrated in FIG. 152 where the following constants are set bysoftware:

The algorithm optionally includes the contributions from previous lightsources, and also includes an ambient light calculation. Ambient lightneeds only to be included once. For all other light passes, theappropriate constant in the Calculate Ambient process should be set to0. The algorithm as shown requires a total of 41 multiply/accumulates.

Print Head 44

FIG. 153 illustrates the logical layout of a single print Head whichlogically consists of 8 segments, each printing bi-level cyan, magenta,and yellow onto a portion of the page.

Loading a Segment for Printing

Before anything can be printed, each of the 8 segments in the Print Headmust be loaded with 6 rows of data corresponding to the followingrelative rows in the final output image:

Row 0=Line N, Yellow, even dots 0, 2, 4, 6, 8, . . . .

Row 1=Line N+8, Yellow, odd dots 1, 3, 5, 7, . . . .

Row 2=Line N+10, Magenta, even dots 0, 2, 4, 6, 8, . . . .

Row 3=Line N+18, Magenta, odd dots 1, 3, 5, 7, . . . .

Row 4=Line N+20, Cyan, even dots 0, 2, 4, 6, 8, . . . .

Row 5=Line N+28, Cyan, odd dots 1, 3, 5, 7, . . . .

Each of the segments prints dots over different parts of the page. Eachsegment prints 750 dots of one color, 375 even dots on one row, and 375odd dots on another. The 8 segments have dots corresponding topositions:

Segment First dot Last dot 0 0 749 1 750 1499 2 1500 2249 3 2250 2999 43000 3749 5 3750 4499 6 4500 5249 7 5250 5999

Each dot is represented in the Print Head segment by a single bit. Thedata must be loaded 1 bit at a time by placing the data on the segment'sBitValue pin, and clocked in to a shift register in the segmentaccording to a BitClock. Since the data is loaded into a shift register,the order of loading bits must be correct. Data can be clocked in to thePrint Head at a maximum rate of 10 MHz.

Once all the bits have been loaded, they must be transferred in parallelto the Print Head output buffer, ready for printing. The transfer isaccomplished by a single pulse on the segment's ParallelXferClock pin.

Controlling the Print

In order to conserve power, not all the dots of the Print Head have tobe printed simultaneously. A set of control lines enables the printingof specific dots. An external controller, such as the ACP, can changethe number of dots printed at once, as well as the duration of the printpulse in accordance with speed and/or power requirements.

Each segment has 5 NozzleSelect lines, which are decoded to select 32sets of nozzles per row. Since each row has 375 nozzles, each setcontains 12 nozzles. There are also 2 BankEnable lines, one for each ofthe odd and even rows of color. Finally, each segment has 3 ColorEnablelines, one for each of C, M, and Y colors. A pulse on one of theColorEnable lines causes the specified nozzles of the color's specifiedrows to be printed. A pulse is typically about 2 s in duration.

If all the segments are controlled by the same set of NozzleSelect,BankEnable and ColorEnable lines (wired externally to the print head),the following is true:

If both odd and even banks print simultaneously (both BankEnable bitsare set), 24 nozzles fire simultaneously per segment, 192 nozzles inall, consuming 5.7 Watts.

If odd and even banks print independently, only 12 nozzles firesimultaneously per segment, 96 in all, consuming 2.85 Watts.

Print Head Interface 62

The Print Head Interface 62 connects the ACP to the Print Head,providing both data and appropriate signals to the external Print Head.The Print Head Interface 62 works in conjunction with both a VLIWprocessor 74 and a software algorithm running on the CPU in order toprint a photo in approximately 2 seconds.

An overview of the inputs and outputs to the Print Head Interface isshown in FIG. 154. The Address and Data Buses are used by the CPU toaddress the various registers in the Print Head Interface. A singleBitClock output line connects to all 8 segments on the print head. The 8DataBits lines lead one to each segment, and are clocked in to the 8segments on the print head simultaneously (on a BitClock pulse). Forexample, dot 0 is transferred to segment₀, dot 750 is transferred tosegment', dot 1500 to segment₂ etc. simultaneously.

The VLIW Output FIFO contains the dithered bi-level C, M, and Y6000×9000 resolution print image in the correct order for output to the8 DataBits. The ParallelXferClock is connected to each of the 8 segmentson the print head, so that on a single pulse, all segments transfertheir bits at the same time. Finally, the NozzleSelect, BankEnable andColorEnable lines are connected to each of the 8 segments, allowing thePrint Head Interface to control the duration of the C, M, and Y droppulses as well as how many drops are printed with each pulse. Registersin the Print Head Interface allow the specification of pulse durationsbetween 0 and 6 μs, with a typical duration of 2 μs.

Printing an Image

There are 2 phases that must occur before an image is in the hand of theArtcam user:

1. Preparation of the image to be printed

2. Printing the prepared image

Preparation of an image only needs to be performed once. Printing theimage can be performed as many times as desired.

Prepare the Image

Preparing an image for printing involves:

1. Convert the Photo Image into a Print Image

2. Rotation of the Print Image (internal color space) to align theoutput for the orientation of the printer

3. Up-interpolation of compressed channels (if necessary)

4. Color conversion from the internal color space to the CMY color spaceappropriate to the specific printer and ink

At the end of image preparation, a 4.5 MB correctly oriented 1000×1500CMY image is ready to be printed.

Convert Photo Image to Print Image

The conversion of a Photo Image into a Print Image requires theexecution of a Vark script to perform image processing. The script iseither a default image enhancement script or a Vark script taken fromthe currently inserted Artcard. The Vark script is executed via the CPU,accelerated by functions performed by the VLIW Vector Processor.

Rotate the Print Image

The image in memory is originally oriented to be top upwards. Thisallows for straightforward Vark processing. Before the image is printed,it must be aligned with the print roll's orientation. The re-alignmentonly needs to be done once. Subsequent Prints of a Print Image willalready have been rotated appropriately.

The transformation to be applied is simply the inverse of that appliedduring capture from the CCD when the user pressed the “Image Capture”button on the Artcam. If the original rotation was 0, then notransformation needs to take place. If the original rotation was +90degrees, then the rotation before printing needs to be −90 degrees (sameas 270 degrees). The method used to apply the rotation is the Varkaccelerated Affine Transform function. The Affine Transform engine canbe called to rotate each color channel independently. Note that thecolor channels cannot be rotated in place. Instead, they can make use ofthe space previously used for the expanded single channel (1.5 MB).

FIG. 155 shows an example of rotation of a Lab image where the a and bchannels are compressed 4:1. The L channel is rotated into the space nolonger required (the single channel area), then the a channel can berotated into the space left vacant by L, and finally the b channel canbe rotated. The total time to rotate the 3 channels is 0.09 seconds. Itis an acceptable period of time to elapse before the first print image.Subsequent prints do not incur this overhead.

Up Interpolate and Color Convert

The Lab image must be converted to CMY before printing. Differentprocessing occurs depending on whether the a and b channels of the Labimage is compressed. If the Lab image is compressed, the a and bchannels must be decompressed before the color conversion occurs. If theLab image is not compressed, the color conversion is the only necessarystep. The Lab image must be up interpolated (if the a and b channels arecompressed) and converted into a CMY image. A single VLIW processcombining scale and color transform can be used.

The method used to perform the color conversion is the Vark acceleratedColor Convert function. The Affine Transform engine can be called torotate each color channel independently. The color channels cannot berotated in place. Instead, they can make use of the space previouslyused for the expanded single channel (1.5 MB).

Print the Image

Printing an image is concerned with taking a correctly oriented1000×1500 CMY image, and generating data and signals to be sent to theexternal Print Head. The process involves the CPU working in conjunctionwith a VLIW process and the Print Head Interface.

The resolution of the image in the Artcam is 1000×1500. The printedimage has a resolution of 6000×9000 dots, which makes for a verystraightforward relationship: 1 pixel=6×6=36 dots. As shown in FIG. 156since each dot is 16.6 μm, the 6×6 dot square is 100 μm square. Sinceeach of the dots is bi-level, the output must be dithered.

The image should be printed in approximately 2 seconds. For 9000 rows ofdots this implies a time of 222 us time between printing each row. ThePrint Head Interface must generate the 6000 dots in this time, anaverage of 37 ns per dot. However, each dot comprises 3 colors, so thePrint Head Interface must generate each color component in approximately12 ns, or 1 clock cycle of the ACP (10 ns at 100 MHz). One VLIW processis responsible for calculating the next line of 6000 dots to be printed.The odd and even C, M, and Y dots are generated by dithering input from6 different 1000×1500 CMY image lines. The second VLIW process isresponsible for taking the previously calculated line of 6000 dots, andcorrectly generating the 8 bits of data for the 8 segments to betransferred by the Print Head Interface to the Print Head in a singletransfer.

A CPU process updates registers in the first VLIW process 3 times perprint line (once per color component=27000 times in 2 seconds), and inthe 2nd VLIW process once every print line (9000 times in 2 seconds).The CPU works one line ahead of the VLIW process in order to do this.

Finally, the Print Head Interface takes the 8 bit data from the VLIWOutput FIFO, and outputs it unchanged to the Print Head, producing theBitClock signals appropriately. Once all the data has been transferred aParallelXferClock signal is generated to load the data for the nextprint line. In conjunction with transferring the data to the Print Head,a separate timer is generating the signals for the different printcycles of the Print Head using the NozzleSelect, ColorEnable, andBankEnable lines a specified by Print Head Interface internal registers.

The CPU also controls the various motors and guillotine via the parallelinterface during the print process.

Generate C, M, and Y Dots

The input to this process is a 1000×1500 CMY image correctly orientedfor printing. The image is not compressed in any way. As illustrated inFIG. 157, a VLIW microcode program takes the CMY image, and generatesthe C, M, and Y pixels required by the Print Head Interface to bedithered.

The process is run 3 times, once for each of the 3 color components. Theprocess consists of 2 sub-processes run in parallel—one for producingeven dots, and the other for producing odd dots. Each sub-process takesone pixel from the input image, and produces 3 output dots (since onepixel=6 output dots, and each sub-process is concerned with either evenor odd dots). Thus one output dot is generated each cycle, but an inputpixel is only read once every 3 cycles.

The original dither cell is a 64×64 cell, with each entry 8 bits. Thisoriginal cell is divided into an odd cell and an even cell, so that eachis still 64 high, but only 32 entries wide. The even dither cellcontains original dither cell pixels 0, 2, 4 etc., while the oddcontains original dither cell pixels 1, 3, 5 etc. Since a dither cellrepeats across a line, a single 32 byte line of each of the 2 dithercells is required during an entire line, and can therefore be completelycached. The odd and even lines of a single process line are staggered 8dot lines apart, so it is convenient to rotate the odd dither cell'slines by 8 lines. Therefore the same offset into both odd and evendither cells can be used. Consequently the even dither cell's linecorresponds to the even entries of line L in the original dither cell,and the even dither cell's line corresponds to the odd entries of lineL+8 in the original dither cell.

The process is run 3 times, once for each of the color components. TheCPU software routine must ensure that the Sequential Read Iterators forodd and even lines are pointing to the correct image lines correspondingto the print heads. For example, to produce one set of 18,000 dots (3sets of 6000 dots):

Yellow even dot line=0, therefore input Yellow image line=0/6=0

Yellow odd dot line=8, therefore input Yellow image line=8/6=1

Magenta even line=10, therefore input Magenta image line=10/6=1

Magenta odd line=18, therefore input Magenta image line=18/6=3

Cyan even line=20, therefore input Cyan image line=20/6=3

Cyan odd line=28, therefore input Cyan image line=28/6=4

Subsequent sets of input image lines are:

Y=[0, 1], M=[1, 3], C=[3, 4]

Y=[0, 1], M=[1, 3], C=[3, 4]

Y=[0, 1], M=[2, 3], C=[3, 5]

Y=[0, 1], M=[2, 3], C=[3, 5]

Y=[0, 2], M=[2, 3], C=[4, 5]

The dither cell data however, does not need to be updated for each colorcomponent. The dither cell for the 3 colors becomes the same, but offsetby 2 dot lines for each component.

The Dithered Output is written to a Sequential Write Iterator, with oddand even dithered dots written to 2 separate outputs. The same two WriteIterators are used for all 3 color components, so that they arecontiguous within the break-up of odd and even dots.

While one set of dots is being generated for a print line, thepreviously generated set of dots is being merged by a second VLIWprocess as described in the next section.

Generate Merged 8 Bit Dot Output

This process, as illustrated in FIG. 158, takes a single line ofdithered dots and generates the 8 bit data stream for output to thePrint Head Interface via the VLIW Output FIFO. The process requires theentire line to have been prepared, since it requires semi-random accessto most of the dithered line at once. The following constant is set bysoftware:

Constant Value K₁ 375

The Sequential Read Iterators point to the line of previously generateddots, with the Iterator registers set up to limit access to a singlecolor component. The distance between subsequent pixels is 375, and thedistance between one line and the next is given to be 1 byte.Consequently 8 entries are read for each “line”. A single “line”corresponds to the 8 bits to be loaded on the print head. The totalnumber of “lines” in the image is set to be 375. With at least 8 cachelines assigned to the Sequential Read Iterator, complete cache coherenceis maintained. Instead of counting the 8 bits, 8 Microcode steps countimplicitly.

The generation process first reads all the entries from the even dots,combining 8 entries into a single byte which is then output to the VLIWOutput FIFO. Once all 3000 even dots have been read, the 3000 odd dotsare read and processed. A software routine must update the address ofthe dots in the odd and even Sequential Read Iterators once per colorcomponent, which equates to 3 times per line. The two VLIW processesrequire all 8 ALUs and the VLIW Output FIFO. As long as the CPU is ableto update the registers as described in the two processes, the VLIWprocessor can generate the dithered image dots fast enough to keep upwith the printer.

Data Card Reader

FIG. 159, there is illustrated on form of card reader 500 which allowsfor the insertion of Artcards 9 for reading. FIG. 158 shows an explodedperspective of the reader of FIG. 159. Cardreader is interconnected to acomputer system and includes a CCD reading mechanism 35. The cardreaderincludes pinch rollers 506, 507 for pinching an inserted Artcard 9. Oneof the roller e.g. 506 is driven by an Artcard motor 37 for theadvancement of the card 9 between the two rollers 506 and 507 at auniformed speed. The Artcard 9 is passed over a series of LED lights 512which are encased within a clear plastic mould 514 having a semicircular cross section. The cross section focuses the light from theLEDs eg 512 onto the surface of the card 9 as it passes by the LEDs 512.From the surface it is reflected to a high resolution linear CCD 34which is constructed to a resolution of approximately 480 dpi. Thesurface of the Artcard 9 is encoded to the level of approximately 1600dpi hence, the linear CCD 34 supersamples the Artcard surface with anapproximately three times multiplier. The Artcard 9 is further driven ata speed such that the linear CCD 34 is able to supersample in thedirection of Artcard movement at a rate of approximately 4800 readingsper inch. The scanned Artcard CCD data is forwarded from the Artcardreader to ACP 31 for processing. A sensor 49, which can comprise a lightsensor acts to detect of the presence of the card 13.

The CCD reader includes a bottom substrate 516, a top substrate 514which comprises a transparent molded plastic. In between the twosubstrates is inserted the linear CCD array 34 which comprises a thinlong linear CCD array constructed by means of semi-conductormanufacturing processes.

Turning to FIG. 160, there is illustrated a side perspective view,partly in section, of an example construction of the CCD reader unit.The series of LEDs e.g. 512 are operated to emit light when a card 9 ispassing across the surface of the CCD reader 34. The emitted light istransmitted through a portion of the top substrate 523. The substrateincludes a portion e.g. 529 having a curved circumference so as to focuslight emitted from LED 512 to a point e.g. 532 on the surface of thecard 9. The focused light is reflected from the point 532 towards theCCD array 34. A series of microlenses e.g. 534, shown in exaggeratedform, are formed on the surface of the top substrate 523. Themicrolenses 523 act to focus light received across the surface to thefocused down to a point 536 which corresponds to point on the surface ofthe CCD reader 34 for sensing of light falling on the light sensingportion of the CCD array 34.

A number of refinements of the above arrangement are possible. Forexample, the sensing devices on the linear CCD 34 may be staggered. Thecorresponding microlenses 34 can also be correspondingly formed as tofocus light into a staggered series of spots so as to correspond to thestaggered CCD sensors.

To assist reading, the data surface area of the Artcard 9 is modulatedwith a checkerboard pattern as previously discussed with reference toFIG. 38. Other forms of high frequency modulation may be possiblehowever.

It will be evident that an Artcard printer can be provided as for theprinting out of data on storage Artcard. Hence, the Artcard system canbe utilized as a general form of information distribution outside of theArtcam device. An Artcard printer can prints out Artcards on highquality print surfaces and multiple Artcards can be printed on samesheets and later separated. On a second surface of the Artcard 9 can beprinted information relating to the files etc. stored on the Artcard 9for subsequent storage.

Hence, the Artcard system allows for a simplified form of storage whichis suitable for use in place of other forms of storage such as CD ROMs,magnetic disks etc. The Artcards 9 can also be mass produced and therebyproduced in a substantially inexpensive form for redistribution.

Print Rolls

Turning to FIG. 162, there is illustrated the print roll 42 andprint-head portions of the Artcam. The paper/film 611 is fed in acontinuous “web-like” process to a printing mechanism 615 which includesfurther pinch rollers 616-619 and a print head 44.

The pinch roller 613 is connected to a drive mechanism (not shown) andupon rotation of the print roller 613, “paper” in the form of film 611is forced through the printing mechanism 615 and out of the pictureoutput slot 6. A rotary guillotine mechanism (not shown) is utilised tocut the roll of paper 611 at required photo sizes.

It is therefore evident that the printer roll 42 is responsible forsupplying “paper” 611 to the print mechanism 615 for printing ofphotographically imaged pictures.

In FIG. 163, there is shown an exploded perspective of the print roll42. The printer roll 42 includes output printer paper 611 which isoutput under the operation of pinching rollers 612, 613.

Referring now to FIG. 164, there is illustrated a more fully explodedperspective view, of the print roll 42 of FIG. 163 without the “paper”film roll. The print roll 42 includes three main parts comprising inkreservoir section 620, paper roll sections 622, 623 and outer casingsections 626, 627. Turning first to the ink reservoir section 620, whichincludes the ink reservoir or ink supply sections 633. The ink forprinting is contained within three bladder type containers 630-632. Theprinter roll 42 is assumed to provide full color output inks Hence, afirst ink reservoir or bladder container 630 contains cyan colored ink.A second reservoir 631 contains magenta colored ink and a thirdreservoir 632 contains yellow ink. Each of the reservoirs 630-632,although having different volumetric dimensions, are designed to havesubstantially the same volumetric size.

The ink reservoir sections 621, 633, in addition to cover 624 can bemade of plastic sections and are designed to be mated together by meansof heat sealing, ultra violet radiation, etc. Each of the equally sizedink reservoirs 630-632 is connected to a corresponding ink channel639-641 for allowing the flow of ink from the reservoir 630-632 to acorresponding ink output port 635-637. The ink reservoir 632 having inkchannel 641, and output port 637, the ink reservoir 631 having inkchannel 640 and output port 636, and the ink reservoir 630 having inkchannel 639 and output port 637.

In operation, the ink reservoirs 630-632 can be filled withcorresponding ink and the section 633 joined to the section 621. The inkreservoir sections 630-632, being collapsible bladders, allow for ink totraverse ink channels 639-641 and therefore be in fluid communicationwith the ink output ports 635-637. Further, if required, an air inletport can also be provided to allow the pressure associated with inkchannel reservoirs 630-632 to be maintained as required.

The cap 624 can be joined to the ink reservoir section 620 so as to forma pressurized cavity, accessible by the air pressure inlet port.

The ink reservoir sections 621, 633 and 624 are designed to be connectedtogether as an integral unit and to be inserted inside printer rollsections 622, 623. The printer roll sections 622, 623 are designed tomate together by means of a snap fit by means of male portions 645-647mating with corresponding female portions (not shown). Similarly, femaleportions 654-656 are designed to mate with corresponding male portions660-662. The paper roll sections 622, 623 are therefore designed to besnapped together. One end of the film within the role is pinched betweenthe two sections 622, 623 when they are joined together. The print filmcan then be rolled on the print roll sections 622, 625 as required.

As noted previously, the ink reservoir sections 620, 621, 633, 624 aredesigned to be inserted inside the paper roll sections 622, 623. Theprinter roll sections 622, 623 are able to be rotatable aroundstationery ink reservoir sections 621, 633 and 624 to dispense film ondemand.

The outer casing sections 626 and 627 are further designed to be coupledaround the print roller sections 622, 623. In addition to each end ofpinch rollers eg 612, 613 is designed to clip in to a correspondingcavity eg 670 in cover 626, 627 with roller 613 being driven externally(not shown) to feed the print film and out of the print roll.

Finally, a cavity 677 can be provided in the ink reservoir sections 620,621 for the insertion and gluing of an silicon chip integrated circuittype device 53 for the storage of information associated with the printroll 42.

As shown in FIG. 155 and FIG. 164, the print roll 42 is designed to beinserted into the Artcam camera device so as to couple with a couplingunit 680 which includes connector pads 681 for providing a connectionwith the silicon chip 53. Further, the connector 680 includes endconnectors of four connecting with ink supply ports 635-637. The inksupply ports are in turn to connect to ink supply lines eg 682 which arein turn interconnected to printheads supply ports e.g. 687 for the flowof ink to print-head 44 in accordance with requirements.

The “media” 611 utilised to form the roll can comprise many differentmaterials on which it is designed to print suitable images. For example,opaque rollable plastic material may be utilized, transparencies may beused by using transparent plastic sheets, metallic printing can takeplace via utilization of a metallic sheet film. Further, fabrics couldbe utilised within the printer roll 42 for printing images on fabric,although care must be taken that only fabrics having a suitablestiffness or suitable backing material are utilised.

When the print media is plastic, it can be coated with a layer whichfixes and absorbs the ink. Further, several types of print media may beused, for example, opaque white matte, opaque white gloss, transparentfilm, frosted transparent film, lenticular array film for stereoscopic3D prints, metallised film, film with the embossed optical variabledevices such as gratings or holograms, media which is pre-printed on thereverse side, and media which includes a magnetic recording layer. Whenutilising a metallic foil, the metallic foil can have a polymer base,coated with a thin (several micron) evaporated layer of aluminum orother metal and then coated with a clear protective layer adapted toreceive the ink via the ink printer mechanism.

In use the print roll 42 is obviously designed to be inserted inside acamera device so as to provide ink and paper for the printing of imageson demand. The ink output ports 635-637 meet with corresponding portswithin the camera device and the pinch rollers 672, 673 are operated toallow the supply of paper to the camera device under the control of thecamera device.

As illustrated in FIG. 164, a mounted silicon chip 53 is insert in oneend of the print roll 42. In FIG. 165 the authentication chip 53 isshown in more detail and includes four communications leads 680-683 forcommunicating details from the chip 53 to the corresponding camera towhich it is inserted.

Turning to FIG. 165, the chip can be separately created by means ofencasing a small integrated circuit 687 in epoxy and running bondingleads e.g. 688 to the external communications leads 680-683. Theintegrated chip 687 being approximately 400 microns square with a 100micron scribe boundary. Subsequently, the chip can be glued to anappropriate surface of the cavity of the print roll 42. In FIG. 166,there is illustrated the integrated circuit 687 interconnected tobonding pads 681, 682 in an exploded view of the arrangement of FIG.165.

In FIGS. 164A to 164E of the drawings, reference numeral 1100 generallydesignates a print cartridge 1100. The print cartridge 1100 includes anink cartridge 1102, in accordance with the invention.

The print cartridge 1100 includes a housing 1104. As illustrated moreclearly in FIG. 2 of the drawings, the housing 1104 is defined by anupper molding 1106 and a lower molding 1108. The moldings 1106 and 1108clip together by means of clips 1110. The housing 1104 is covered by alabel 1112 which provides an attractive appearance to the cartridge1100. The label 1112 also carries information to enable a user to usethe cartridge 1100.

The housing 1104 defines a chamber 1114 in which the ink cartridge 1102is received. The ink cartridge 1102 is fixedly supported in the chamber1114 of the housing 1104.

A supply of print media 1116 comprising a roll 1126 of film/media 1118wound about a former 1120 is received in the chamber 1114 of the housing1104. The former 1120 is slidably received over the ink cartridge 1102and is rotatable relative thereto.

As illustrated in FIG. 164B of the drawings, when the upper molding 1106and lower molding 1108 are clipped together, an exit slot 1122 isdefined through which a tongue of the paper 1118 is ejected.

The cartridge 1100 includes a roller assembly 1124 which serves tode-curl the paper 1118 as it is fed from the roll 1126 and also to drivethe paper 1118 through the slot 1122. The roller assembly 1124 includesa drive roller 1128 and two driven rollers 1130. The driven rollers 1130are rotatably supported in ribs 1132 which stand proud of a floor 1134of the lower molding 1108 of the housing 1104. The rollers 1130,together with the drive roller 1128, provide positive traction to thepaper 1118 to control its speed and position as it is ejected from thehousing 1104. The rollers 1130 are injection moldings of a suitablesynthetic plastics material such as polystyrene. In this regard also,the upper molding 1106 and the lower molding 1108 are injection moldingsof suitable synthetic plastics material, such as polystyrene.

The drive roller 1128 includes a drive shaft 1136 which is heldrotatably captive between mating recesses 1138 and 1140 defined in aside wall of each of the upper molding 1106 and the lower molding 1108,respectively, of the housing 1104. An opposed end 1142 of the driveroller 1128 is held rotatably in suitable formations (not shown) in theupper molding 1106 and the lower molding 1108 of the housing 1104.

The drive roller 1128 is a two shot injection molding comprising theshaft 1136 which is of a high impact polystyrene and on which are moldeda bearing means in the form of elastomeric or rubber roller portions1144. These portions 1144 positively engage the paper 1118 and inhibitslippage of the paper 1118 as the paper 1118 is fed from the cartridge1100.

The end of the roller 1128 projecting from the housing 1104 has anengaging formation in the form of a cruciform arrangement 1146 (FIG.164A) which mates with a geared drive interface (not shown) of aprinthead assembly of a device, such as a camera, in which the printcartridge 1100 is installed. This arrangement ensures that the speed atwhich the paper 1118 is fed to the printhead is synchronised withprinting by the printhead to ensure accurate registration of ink on thepaper 1118.

The ink cartridge 1102 includes a container 1148 which is in the form ofa right circular cylindrical extrusion. The container 1148 is extrudedfrom a suitable synthetic plastics material such as polystyrene.

In a preferred embodiment of the invention, the printhead with which theprint cartridge 1100 is used, is a multi-colored printhead. Accordingly,the container 1148 is divided into a plurality of, more particularly,four compartments or reservoirs 1150. Each reservoir 1150 houses adifferent color or type of ink. In one embodiment, the inks contained inthe reservoirs 1150 are cyan, magenta, yellow and black inks In anotherembodiment of the invention, three different colored inks, being cyan,magenta and yellow inks, are accommodated in three of the reservoirs1150 while a fourth reservoir 1150 houses an ink which is visible in theinfra-red light spectrum only.

As shown more clearly in FIGS. 164C and 164D of the drawings, one end ofthe container 1148 is closed off by an end cap 1152. The end cap 1152has a plurality of openings 1154 defined in it. An opening 1154 isassociated with each reservoir 1150 so that atmospheric pressure ismaintained in the reservoir 1150 at that end of the container 1148having the end cap 1152.

A seal arrangement 1156 is received in the container 1148 at the endhaving the end cap 1152. The seal arrangement 1156 comprises a quadrantshaped pellet 1158 of gelatinous material slidably received in eachreservoir 1150. The gelatinous material of the pellet 1158 is a compoundmade of a thermoplastic rubber and a hydrocarbon. The hydrocarbon is awhite mineral oil. The thermoplastic rubber is a copolymer which impartssufficient rigidity to the mineral oil so that the pellet 1158 retainsits form at normal operating temperatures while permitting sliding ofthe pellet 1158 within its associated reservoir 1150. A suitablethermoplastic rubber is that sold under the registered trademark of“Kraton” by the Shell Chemical Company. The copolymer is present in thecompound in an amount sufficient to impart a gel-like consistency toeach pellet 1158. Typically, the copolymer, depending on the type used,would be present in an amount of approximately three percent to twentypercent by mass.

In use, the compound is heated so that it becomes fluid. Once eachreservoir 1150 has been charged with its particular type of ink, thecompound, in a molten state, is poured into each reservoir 1150 wherethe compound is allowed to set to form the pellet 1158. Atmosphericpressure behind the pellets 1158, that is, at that end of the pellet1158 facing the end cap 1152 ensures that, as ink is withdrawn from thereservoir 1150, the pellets 1158, which are self-lubricating, slidetowards an opposed end of the container 1148. The pellets 1158 stop inkemptying out of the container when inverted, inhibit contamination ofthe ink in the reservoir 1150 and also inhibit drying out of the ink inthe reservoir 1150. The pellets 1158 are hydrophobic further to inhibitleakage of ink from the reservoirs 1150.

The opposed end of the container 1148 is closed off by an ink collarmolding 1160. Baffles 1162 carried on the molding 1160 receive anelastomeric seal molding 1164. The elastomeric seal molding 1164, whichis hydrophobic, has sealing curtains 1166 defined therein. Each sealingcurtain 1166 has a slit 1168 so that a mating pin (not shown) from theprinthead assembly is insertable through the slits 1168 into fluidcommunication with the reservoirs 1150 of the container 1148. Hollowbosses 1170 project from an opposed side of the ink collar molding 1160.Each boss 1170 is shaped to fit snugly in its associated reservoir 1150for locating the ink collar molding on the end of the container 1148.

Reverting again to FIG. 164C of the drawings, the ink collar molding1160 is retained in place by means of a carrier or fascia molding 1172.The fascia molding 1172 has a four leaf clover shaped window 1174defined therein through which the elastomeric seal molding 1164 isaccessible. The fascia molding 1174 is held captive between the uppermolding 1106 and the lower molding 1108 of the housing 1104. The fasciamolding 1174 and webs 1176 and 1178 extending from an interior surfaceof the upper molding 1106 and the lower molding 1108 respectively, ofthe housing 1104 define a compartment 1180. An air filter 1182 isreceived in the compartment 1180 and is retained in place by the endmolding 1174. The air filter 1182 cooperates with the printheadassembly. Air is blown across a nozzle guard of a printhead assembly toeffect cleaning of the nozzle guard. This air is filtered by being drawnthrough the air filter 1182 by means of a pin (not shown) which isreceived in an inlet opening 1184 in the fascia molding 1172.

The air filter 1182 is shown in greater detail in FIG. 164E of thedrawings. The air filter 1182 comprises a filter medium 1192. The filtermedium 1192 is synthetic fibre based and is arranged in a fluted form toincrease the surface area available for filtering purposes. Instead of apaper based filter medium 1192 other fibrous batts could also be used.

The filter medium 1192 is received in a canister 1194. The canister 1194includes a base molding 1196 and a lid 1198. To be accommodated in thecompartment 1180 of the housing 1104, the canister 1194 is part-annularor horse shoe shaped. Thus, the canister 1194 has a pair of opposed ends1200. An air inlet opening 1202 is defined in each end 1200. An airoutlet opening 1204 is defined in the lid 1198. The air outlet opening1204, initially, is closed off by a film or membrane 1206. When thefilter 1182 is mounted in position in the compartment 1180, the airoutlet opening 1204 is in register with the opening 1184 in the fasciamolding 1172. The pin from the printhead assembly pierces the film 1206then draws air from the atmosphere through the air filter 1182 prior tothe air being blown over the nozzle guard and the printhead of theprinthead assembly.

The base molding 1194 includes locating formations 1208 and 1210 forlocating the filter medium 1192 in position in the canister 1194. Thelocating formations 1208 are in the form of a plurality of pins 1212while the locating formations 1210 are in the form of ribs which engageends 1214 of the filter medium 1192.

Once the filter medium 1192 has been placed in position in the base mold1196, the lid 1198 is secured to the base molding 1196 by ultrasonicwelding or similar means to seal the lid 1198 to the base molding 1196.

When the print cartridge 1100 has been assembled, a membrane or film1186 is applied to an outer end of the fascia molding 1172 to close offthe window 1174. This membrane or film 1186 is pierced or ruptured bythe pins, for use. The film 1186 inhibits the ingress of detritus intothe ink reservoirs 1150.

An authentication means in the form of an authentication chip 1188 isreceived in an opening 1190 in the fascia molding 1172. Theauthentication chip 1188 is interrogated by the printhead assembly 1188to ensure that the print cartridge 1100 is compatible and compliant withthe printhead assembly of the device.

In FIG. 164F, reference numeral 1230 generally indicates a furtherembodiment of a printing cartridge, in accordance with the invention.With reference to the preceding drawings, like reference numerals referto like parts, unless otherwise specified.

A barcode 1232 is depicted on a housing 1234 of the printing cartridge1230. The barcode 1232 carries data relating to media and ink within thecartridge 1230. The data can relate to a number of characteristics ofthe media and ink. For example, the data can relate to:

(a) Serial numbers identifying the media and the ink;(b) A length of the media in the housing 1234;(c) A type of the media in the housing 1234;(d) Physical characteristics of the ink such as surface tension andviscosity;(e) Optical characteristics of the ink, such as optical density of redgreen and blue components;(f) A preferred ink drop volume to suit the media type.

It will be appreciated that other forms of data can also be carried bythe barcode 1232.

A barcode scanner 1236 is positioned so that, when the cartridge 1230 isinserted into the Artcam device, the barcode scanner 1236 scans thebarcode 1232. The barcode scanner 1236 thus generates a signal which isreceived by a barcode scanner interface 1238 positioned on the Artcamcentral processor (ACP) 31 (FIG. 3A). The barcode scanner 1236 is alsoshown schematically in FIG. 2. It follows that the barcode scanner 1236and the barcode scanner interface 1236 together define a linear barcodereader.

The barcode scanner interface 1238 operates in a similar fashion to theother interfaces 83, 87 in that it serves to convert the signal receivedfrom the barcode scanner 1236 into a signal which is readable by the CPUcore 72.

The CPU core 72 is configured so that it can control the manner ofoperation of the printhead 44 depending on the data received from thebarcode scanner interface 1238. This allows operation of the printhead44 to be optimized to suit the media and/or the ink in the housing 1234.

It will be appreciated by those skilled in the art that the amount ofdata that can be represented by the barcode 1236 is limited. It followsthat the CPU core 72 is configured to hold data lookup tables in amemory.

An example of such a lookup table is indicated by reference numeral 1240in FIG. 164G. As can be seen, the table 1240 represents the above typesof data. The memory contains a plurality of different values for each ofthe data types listed in the data lookup table 1240 as a₁, . . . ,a_(n), b₁, . . . , b_(n), c₁, . . . , c_(n), d₁, . . . d_(n), e₁, . . .e_(n), f₁, . . . , f_(n), g₁, . . . , g_(n), respectively. Each of thesevalues is predetermined to correspond with possible values relating tomedia and ink corresponding to those found in the range of inks andmedia types which could be found in the cartridge.

Each of the possible values is represented by a code indicated by x₁,x₂, . . . , x_(n) in the lookup table 1240. The codes are not dividedinto different data types and each code is therefore unique to itsparticular associated value in the lookup table 1240.

The barcode 1232 defines a number of codes x_(i), x_(j), x_(k), x_(l),x_(m), x_(n), x_(o) representing a value of each of the data types. Analgorithm is used to look up the data relating to the actual valuerepresented by these codes. It will thus be appreciated that thenecessity for the barcode to carry a substantial amount of informationis obviated.

The data carried by the barcode 1232 can be encrypted with one of thetechniques described below.

Authentication Chip Authentication Chips 53

The authentication chip 53 of the preferred embodiment is responsiblefor ensuring that only correctly manufactured print rolls are utilizedin the camera system. The authentication chip 53 utilizes technologiesthat are generally valuable when utilized with any consumables and arenot restricted to print roll system. Manufacturers of other systems thatrequire consumables (such as a laser printer that requires tonercartridges) have struggled with the problem of authenticatingconsumables, to varying levels of success. Most have resorted tospecialized packaging. However this does not stop home refill operationsor clone manufacture. The prevention of copying is important to preventpoorly manufactured substitute consumables from damaging the basesystem. For example, poorly filtered ink may clog print nozzles in anink jet printer, causing the consumer to blame the system manufacturerand not admit the use of non-authorized consumables.

To solve the authentication problem, the Authentication chip 53 containsan authentication code and circuit specially designed to preventcopying. The chip is manufactured using the standard Flash memorymanufacturing process, and is low cost enough to be included inconsumables such as ink and toner cartridges. Once programmed, theAuthentication chips as described here are compliant with the NSA exportguidelines. Authentication is an extremely large and constantly growingfield. Here we are concerned with authenticating consumables only.

Symbolic Nomenclature

The following symbolic nomenclature is used throughout the discussion ofthis embodiment:

Symbolic Nomenclature Description F[X] Function F, taking a singleparameter X F[X, Y] Function F, taking two parameters, X and Y X | Y Xconcatenated with Y X

 Y Bitwise X AND Y X

 Y Bitwise X OR Y (inclusive-OR) X⊕Y Bitwise X XOR Y (exclusive-OR) ~XBitwise NOT X (complement) X ← Y X is assigned the value Y X ← {Y, Z}The domain of assignment inputs to X is Y and Z. X = Y X is equal to Y X≠ Y X is not equal to Y

X Decrement X by 1 (floor 0) X Increment X by 1 (with wrapping based onregister length) Erase X Erase Flash memory register X SetBits[X, Y] Setthe bits of the Flash memory register X based on Y Z ← ShiftRight[X, Y]Shift register X right one bit position, taking input bit from Y andplacing the output bit in Z

Basic Terms

A message, denoted by M, is plaintext. The process of transforming Minto cyphertext C, where the substance of M is hidden, is calledencryption. The process of transforming C back into M is calleddecryption. Referring to the encryption function as E, and thedecryption function as D, we have the following identities:

-   -   E[M]=C    -   D[C]=M

Therefore the following identity is true:

-   -   D[E[M]]=M

Symmetric Cryptography

A symmetric encryption algorithm is one where:

-   -   the encryption function E relies on key K₁,    -   the decryption function D relies on key K₂,    -   K₂ can be derived from K₁, and    -   K₁ can be derived from K₂.

In most symmetric algorithms, K₁ usually equals K₂. However, even if K₁does not equal K₂, given that one key can be derived from the other, asingle key K can suffice for the mathematical definition. Thus:

-   -   E_(K)[M]=C    -   D_(K)[C]=M

An enormous variety of symmetric algorithms exist, from the textbooks ofancient history through to sophisticated modern algorithms. Many ofthese are insecure, in that modern cryptanalysis techniques cansuccessfully attack the algorithm to the extent that K can be derived.The security of the particular symmetric algorithm is normally afunction of two things: the strength of the algorithm and the length ofthe key. The following algorithms include suitable aspects forutilization in the authentication chip.

-   -   DES    -   Blowfish    -   RC5    -   IDEA

DES

DES (Data Encryption Standard) is a US and international standard, wherethe same key is used to encrypt and decrypt. The key length is 56 bits.It has been implemented in hardware and software, although the originaldesign was for hardware only. The original algorithm used in DES isdescribed in U.S. Pat. No. 3,962,539. A variant of DES, calledtriple-DES is more secure, but requires 3 keys: K₁, K₂, and K₃. The keysare used in the following manner:

-   -   E_(K3)[D_(K2)[E_(K1)[M]]]=C    -   D_(K3)[E_(K2)[D_(K1)[C]]]=M

The main advantage of triple-DES is that existing DES implementationscan be used to give more security than single key DES. Specifically,triple-DES gives protection of equivalent key length of 112 bits.Triple-DES does not give the equivalent protection of a 168-bit key(3×56) as one might naively expect. Equipment that performs triple-DESdecoding and/or encoding cannot be exported from the United States.

Blowfish

Blowfish, is a symmetric block cipher first presented by Schneier in1994. It takes a variable length key, from 32 bits to 448 bits. Inaddition, it is much faster than DES. The Blowfish algorithm consists oftwo parts: a key-expansion part and a data-encryption part. Keyexpansion converts a key of at most 448 bits into several subkey arraystotaling 4168 bytes. Data encryption occurs via a 16-round Feistelnetwork. All operations are XORs and additions on 32-bit words, withfour index array lookups per round. It should be noted that decryptionis the same as encryption except that the subkey arrays are used in thereverse order. Complexity of implementation is therefore reducedcompared to other algorithms that do not have such symmetry.

RC5

Designed by Ron Rivest in 1995, RC5 has a variable block size, key size,and number of rounds. Typically, however, it uses a 64-bit block sizeand a 128-bit key. The RC5 algorithm consists of two parts: akey-expansion part and a data-encryption part. Key expansion converts akey into 2r+2 subkeys (where r=the number of rounds), each subkey beingw bits. For a 64-bit blocksize with 16 rounds (w=32, r=16), the subkeyarrays total 136 bytes. Data encryption uses addition mod 2^(w), XOR andbitwise rotation.

IDEA

Developed in 1990 by Lai and Massey, the first incarnation of the IDEAcipher was called PES. After differential cryptanalysis was discoveredby Biham and Shamir in 1991, the algorithm was strengthened, with theresult being published in 1992 as IDEA. IDEA uses 128 bit-keys tooperate on 64-bit plaintext blocks. The same algorithm is used forencryption and decryption. It is generally regarded to be the mostsecure block algorithm available today. It is described in U.S. Pat. No.5,214,703, issued in 1993.

Asymmetric Cryptography

As alternative an asymmetric algorithm could be used. An asymmetricencryption algorithm is one where:

-   -   the encryption function E relies on key K₁,    -   the decryption function D relies on key K₂,    -   K₂ cannot be derived from K₁ in a reasonable amount of time, and    -   K₁ cannot be derived from K₂ in a reasonable amount of time.

Thus:

-   -   E_(K1)[M]=C    -   D_(K2)[C]=M

These algorithms are also called public-key because one key K₁ can bemade public. Thus anyone can encrypt a message (using K₁), but only theperson with the corresponding decryption key (K₂) can decrypt and thusread the message. In most cases, the following identity also holds:

-   -   E_(K2)[M]=C    -   D_(K1)[C]=M

This identity is very important because it implies that anyone with thepublic key K₁ can see M and know that it came from the owner of K₂.No-one else could have generated C because to do so would implyknowledge of K₂. The property of not being able to derive K₁ from K₂ andvice versa in a reasonable time is of course clouded by the concept ofreasonable time. What has been demonstrated time after time, is that acalculation that was thought to require a long time has been madepossible by the introduction of faster computers, new algorithms etc.The security of asymmetric algorithms is based on the difficulty of oneof two problems: factoring large numbers (more specifically largenumbers that are the product of two large primes), and the difficulty ofcalculating discrete logarithms in a finite field. Factoring largenumbers is conjectured to be a hard problem given today's understandingof mathematics. The problem however, is that factoring is getting easiermuch faster than anticipated. Ron Rivest in 1977 said that factoring a125-digit number would take 40 quadrillion years. In 1994 a 129-digitnumber was factored. According to Schneier, you need a 1024-bit numberto get the level of security today that you got from a 512-bit number inthe 1980's. If the key is to last for some years then 1024 bits may noteven be enough. Rivest revised his key length estimates in 1990: hesuggests 1628 bits for high security lasting until 2005, and 1884 bitsfor high security lasting until 2015. By contrast, Schneier suggests2048 bits are required in order to protect against corporations andgovernments until 2015.

A number of public key cryptographic algorithms exist. Most areimpractical to implement, and many generate a very large C for a given Mor require enormous keys. Still others, while secure, are far too slowto be practical for several years. Because of this, many public-keysystems are hybrid—a public key mechanism is used to transmit asymmetric session key, and then the session key is used for the actualmessages. All of the algorithms have a problem in terms of keyselection. A random number is simply not secure enough. The two largeprimes p and q must be chosen carefully—there are certain weakcombinations that can be factored more easily (some of the weak keys canbe tested for). But nonetheless, key selection is not a simple matter ofrandomly selecting 1024 bits for example. Consequently the key selectionprocess must also be secure.

Of the practical algorithms in use under public scrutiny, the followingmay be suitable for utilization:

-   -   RSA    -   DSA    -   ElGamal

RSA

The RSA cryptosystem, named after Rivest, Shamir, and Adleman, is themost widely used public-key cryptosystem, and is a de facto standard inmuch of the world. The security of RSA is conjectured to depend on thedifficulty of factoring large numbers that are the product of two primes(p and q). There are a number of restrictions on the generation of p andq. They should both be large, with a similar number of bits, yet not beclose to one another (otherwise pq≈√pq). In addition, many authors havesuggested that p and q should be strong primes. The RSA algorithm patentwas issued in 1983 (U.S. Pat. No. 4,405,829).

DSA

DSA (Digital Signature Standard) is an algorithm designed as part of theDigital Signature Standard (DSS). As defined, it cannot be used forgeneralized encryption. In addition, compared to RSA, DSA is 10 to 40times slower for signature verification. DSA explicitly uses the SHA-1hashing algorithm (see definition in

One-way Functions below). DSA key generation relies on finding twoprimes p and q such that q divides p−1. According to Schneier, a1024-bit p value is required for long term DSA security. However the DSAstandard does not permit values of p larger than 1024 bits (p must alsobe a multiple of 64 bits). The US Government owns the DSA algorithm andhas at least one relevant patent (U.S. Pat. No. 5,231,688 granted in1993).

ElGamal

The ElGamal scheme is used for both encryption and digital signatures.The security is based on the difficulty of calculating discretelogarithms in a finite field. Key selection involves the selection of aprime p, and two random numbers g and x such that both g and x are lessthan p. Then calculate y=gx mod p. The public key is y, g, and p. Theprivate key is x.

Cryptographic Challenge-Response Protocols and Zero Knowledge Proofs

The general principle of a challenge-response protocol is to provideidentity authentication adapted to a camera system. The simplest form ofchallenge-response takes the form of a secret password. A asks B for thesecret password, and if B responds with the correct password, A declaresB authentic. There are three main problems with this kind of simplisticprotocol. Firstly, once B has given out the password, any observer Cwill know what the password is. Secondly, A must know the password inorder to verify it. Thirdly, if C impersonates A, then B will give thepassword to C (thinking C was A), thus compromising B. Using a copyrighttext (such as a haiku) is a weaker alternative as we are assuming thatanyone is able to copy the password (for example in a country whereintellectual property is not respected). The idea of cryptographicchallenge-response protocols is that one entity (the claimant) provesits identity to another (the verifier) by demonstrating knowledge of asecret known to be associated with that entity, without revealing thesecret itself to the verifier during the protocol. In the generalizedcase of cryptographic challenge-response protocols, with some schemesthe verifier knows the secret, while in others the secret is not evenknown by the verifier. Since the discussion of this embodimentspecifically concerns Authentication, the actual cryptographicchallenge-response protocols used for authentication are detailed in theappropriate sections. However the concept of Zero Knowledge Proofs willbe discussed here. The Zero Knowledge Proof protocol, first described byFeige, Fiat and Shamir is extensively used in Smart Cards for thepurpose of authentication. The protocol's effectiveness is based on theassumption that it is computationally infeasible to compute square rootsmodulo a large composite integer with unknown factorization. This isprovably equivalent to the assumption that factoring large integers isdifficult. It should be noted that there is no need for the claimant tohave significant computing power. Smart cards implement this kind ofauthentication using only a few modular multiplications. The ZeroKnowledge Proof protocol is described in U.S. Pat. No. 4,748,668.

One-Way Functions

A one-way function F operates on an input X, and returns F[X] such thatX cannot be determined from F[X]. When there is no restriction on theformat of X, and F[X] contains fewer bits than X, then collisions mustexist. A collision is defined as two different X input values producingthe same F[X] value—i.e. X₁ and X₂ exist such that X₁≠X₂ yetF[X₁]=F[X₂]. When X contains more bits than F[X], the input must becompressed in some way to create the output. In many cases, X is brokeninto blocks of a particular size, and compressed over a number ofrounds, with the output of one round being the input to the next. Theoutput of the hash function is the last output once X has been consumed.A pseudo-collision of the compression function CF is defined as twodifferent initial values V₁ and V₂ and two inputs X₁ and X₂ (possiblyidentical) are given such that CF(V₁, X₁)=CF(V₂, X₂). Note that theexistence of a pseudo-collision does not mean that it is easy to computean X₂ for a given X₁.

We are only interested in one-way functions that are fast to compute. Inaddition, we are only interested in deterministic one-way functions thatare repeatable in different implementations. Consider an example F whereF[X] is the time between calls to F. For a given F[X] X cannot bedetermined because X is not even used by F. However the output from Fwill be different for different implementations. This kind of F istherefore not of interest.

In the scope of the discussion of the implementation of theauthentication chip of this embodiment, we are interested in thefollowing forms of one-way functions:

-   -   Encryption using an unknown key    -   Random number sequences    -   Hash Functions    -   Message Authentication Codes

Encryption Using an Unknown Key

When a message is encrypted using an unknown key K, the encryptionfunction E is effectively one-way. Without the key, it iscomputationally infeasible to obtain M from E_(K)[M] without K. Anencryption function is only one-way for as long as the key remainshidden. An encryption algorithm does not create collisions, since Ecreates E_(K)[M] such that it is possible to reconstruct M usingfunction D. Consequently F[X] contains at least as many bits as X (noinformation is lost) if the one-way function F is E. Symmetricencryption algorithms (see above) have the advantage over Asymmetricalgorithms for producing one-way functions based on encryption for thefollowing reasons:

-   -   The key for a given strength encryption algorithm is shorter for        a symmetric algorithm than an asymmetric algorithm    -   Symmetric algorithms are faster to compute and require less        software/silicon

The selection of a good key depends on the encryption algorithm chosen.Certain keys are not strong for particular encryption algorithms, so anykey needs to be tested for strength. The more tests that need to beperformed for key selection, the less likely the key will remain hidden.

Random Number Sequences

Consider a random number sequence R₀, R₁, . . . , R_(I), R_(i+1). Wedefine the one-way function F such that F[X] returns the X^(th) randomnumber in the random sequence. However we must ensure that F[X] isrepeatable for a given X on different implementations. The random numbersequence therefore cannot be truly random. Instead, it must bepseudo-random, with the generator making use of a specific seed.

There are a large number of issues concerned with defining good randomnumber generators. Knuth, describes what makes a generator “good”(including statistical tests), and the general problems associated withconstructing them. The majority of random number generators produce thei^(th) random number from the i−1^(th) state—the only way to determinethe i^(th) number is to iterate from the 0^(th) number to the i^(th). Ifi is large, it may not be practical to wait for i iterations. Howeverthere is a type of random number generator that does allow randomaccess. Blum, Blum and Shub define the ideal generator as follows: “ . .. we would like a pseudo-random sequence generator to quickly produce,from short seeds, long sequences (of bits) that appear in every way tobe generated by successive flips of a fair coin”. They defined the x²mod n generator, more commonly referred to as the BBS generator. Theyshowed that given certain assumptions upon which modern cryptographyrelies, a BBS generator passes extremely stringent statistical tests.

The BBS generator relies on selecting n which is a Blum integer (n=pqwhere p and q are large prime numbers, p≠q, p mod 4=3, and q mod 4=3).The initial state of the generator is given by x₀ where x₀=x² mod n, andx is a random integer relatively prime to n. The i^(th) pseudo-randombit is the least significant bit of x_(i) where x_(i)=x_(i−1) ² mod n.As an extra property, knowledge of p and q allows a direct calculationof the i^(th) number in the sequence as follows: x_(i)=x₀ ^(y) mod n,where y=2^(t) mod((p−1)(q−1))

Without knowledge of p and q, the generator must iterate (the securityof calculation relies on the difficulty of factoring large numbers).When first defined, the primary problem with the BBS generator was theamount of work required for a single output bit. The algorithm wasconsidered too slow for most applications. However the advent ofMontgomery reduction arithmetic has given rise to more practicalimplementations. In addition, Vazirani and Vazirani have shown thatdepending on the size of n, more bits can safely be taken from x_(i)without compromising the security of the generator. Assuming we onlytake 1 bit per x_(i), N bits (and hence N iterations of the bitgenerator function) are needed in order to generate an N-bit randomnumber. To the outside observer, given a particular set of bits, thereis no way to determine the next bit other than a 50/50 probability. Ifthe x, p and q are hidden, they act as a key, and it is computationallyunfeasible to take an output bit stream and compute x, p, and q. It isalso computationally unfeasible to determine the value of i used togenerate a given set of pseudo-random bits. This last feature makes thegenerator one-way. Different values of i can produce identical bitsequences of a given length (e.g. 32 bits of random bits). Even if x, pand q are known, for a given F[i], i can only be derived as a set ofpossibilities, not as a certain value (of course if the domain of i isknown, then the set of possibilities is reduced further). However, thereare problems in selecting a good p and q, and a good seed x. Inparticular, Ritter describes a problem in selecting x. The nature of theproblem is that a BBS generator does not create a single cycle of knownlength. Instead, it creates cycles of various lengths, includingdegenerate (zero-length) cycles. Thus a BBS generator cannot beinitialized with a random state—it might be on a short cycle.

Hash Functions

Special one-way functions, known as Hash functions map arbitrary lengthmessages to fixed-length hash values. Hash functions are referred to asH[M]. Since the input is arbitrary length, a hash function has acompression component in order to produce a fixed length output. Hashfunctions also have an obfuscation component in order to make itdifficult to find collisions and to determine information about M fromH[M]. Because collisions do exist, most applications require that thehash algorithm is preimage resistant, in that for a given X₁ it isdifficult to find X₂ such that H[X₁]=H[X₂]. In addition, mostapplications also require the hash algorithm to be collision resistant(i.e. it should be hard to find two messages X₁ and X₂ such thatH[X₁]=H[X₂]). It is an open problem whether a collision-resistant hashfunction, in the idealist sense, can exist at all. The primaryapplication for hash functions is in the reduction of an input messageinto a digital “fingerprint” before the application of a digitalsignature algorithm. One problem of collisions with digital signaturescan be seen in the following example.

-   -   A has a long message M₁ that says “I owe B $10”. A signs H[M₁]        using his private key. B, being greedy, then searches for a        collision message M₂ where H[M₂]=H[M₁] but where M₂ is favorable        to B, for example “I owe B $1 million”. Clearly it is in A's        interest to ensure that it is difficult to find such an M₂.

Examples of collision resistant one-way hash functions are SHA-1, MD5and RIPEMD-160, all derived from MD4.

MD4

Ron Rivest introduced MD4 in 1990. It is mentioned here because allother one-way hash functions are derived in some way from MD4. MD4 isnow considered completely broken in that collisions can be calculatedinstead of searched for. In the example above, B could triviallygenerate a substitute message M₂ with the same hash value as theoriginal message M₁.

MD5

Ron Rivest introduced MD5 in 1991 as a more secure MD4. Like MD4, MD5produces a 128-bit hash value. Dobbertin describes the status of MD5after recent attacks. He describes how pseudo-collisions have been foundin MD5, indicating a weakness in the compression function, and morerecently, collisions have been found. This means that MD5 should not beused for compression in digital signature schemes where the existence ofcollisions may have dire consequences. However MD5 can still be used asa one-way function. In addition, the HMAC-MD5 construct is not affectedby these recent attacks.

SHA-1

SHA-1 is very similar to MD5, but has a 160-bit hash value (MD5 only has128 bits of hash value). SHA-1 was designed and introduced by the NISTand NSA for use in the Digital Signature Standard (DSS). The originalpublished description was called SHA, but very soon afterwards, wasrevised to become SHA-1, supposedly to correct a security flaw in SHA(although the NSA has not released the mathematical reasoning behind thechange). There are no known cryptographic attacks against SHA-1. It isalso more resistant to brute-force attacks than MD4 or MD5 simplybecause of the longer hash result. The US Government owns the SHA-1 andDSA algorithms (a digital signature authentication algorithm defined aspart of DSS) and has at least one relevant patent (U.S. Pat. No.5,231,688 granted in 1993).

RIPEMD-160

RIPEMD-160 is a hash function derived from its predecessor RIPEMD(developed for the European Community's RIPE project in 1992). As itsname suggests, RIPEMD-160 produces a 160-bit hash result. Tuned forsoftware implementations on 32-bit architectures, RIPEMD-160 is intendedto provide a high level of security for 10 years or more. Although therehave been no successful attacks on RIPEMD-160, it is comparatively newand has not been extensively cryptanalyzed. The original RIPEMDalgorithm was specifically designed to resist known cryptographicattacks on MD4. The recent attacks on MD5 showed similar weaknesses inthe RIPEMD 128-bit hash function. Although the attacks showed onlytheoretical weaknesses, Dobbertin, Preneel and Bosselaers furtherstrengthened RIPEMD into a new algorithm RIPEMD-160.

Message Authentication Codes

The problem of message authentication can be summed up as follows:

-   -   How can A be sure that a message supposedly from B is in fact        from B?

Message authentication is different from entity authentication. Withentity authentication, one entity (the claimant) proves its identity toanother (the verifier). With message authentication, we are concernedwith making sure that a given message is from who we think it is fromi.e. it has not been tampered en route from the source to itsdestination. A one-way hash function is not sufficient protection for amessage. Hash functions such as MD5 rely on generating a hash value thatis representative of the original input, and the original input cannotbe derived from the hash value. A simple attack by E, who is in-betweenA and B, is to intercept the message from B, and substitute his own.Even if A also sends a hash of the original message, E can simplysubstitute the hash of his new message. Using a one-way hash functionalone, A has no way of knowing that B's message has been changed. Onesolution to the problem of message authentication is the MessageAuthentication Code, or MAC. When B sends message M, it also sendsMAC[M] so that the receiver will know that M is actually from B. Forthis to be possible, only B must be able to produce a MAC of M, and inaddition, A should be able to verify M against MAC[M]. Notice that thisis different from encryption of M—MACs are useful when M does not haveto be secret. The simplest method of constructing a MAC from a hashfunction is to encrypt the hash value with a symmetric algorithm:

Hash the input message H[M]Encrypt the hash E_(K)[H[M]]

This is more secure than first encrypting the message and then hashingthe encrypted message. Any symmetric or asymmetric cryptographicfunction can be used. However, there are advantages to using akey-dependant one-way hash function instead of techniques that useencryption (such as that shown above):

-   -   Speed, because one-way hash functions in general work much        faster than encryption;    -   Message size, because E_(K)[H[M]] is at least the same size as        M, while H[M] is a fixed size (usually considerably smaller than        M);    -   Hardware/software requirements—keyed one-way hash functions are        typically far less complexity than their encryption-based        counterparts; and    -   One-way hash function implementations are not considered to be        encryption or decryption devices and therefore are not subject        to US export controls.

It should be noted that hash functions were never originally designed tocontain a key or to support message authentication. As a result, some adhoc methods of using hash functions to perform message authentication,including various functions that concatenate messages with secretprefixes, suffixes, or both have been proposed. Most of these ad hocmethods have been successfully attacked by sophisticated means.Additional MACs have been suggested based on XOR schemes and Toeplitzmatricies (including the special case of LFSR-based constructions).

HMAC

The HMAC construction in particular is gaining acceptance as a solutionfor Internet message authentication security protocols. The HMACconstruction acts as a wrapper, using the underlying hash function in ablack-box way. Replacement of the hash function is straightforward ifdesired due to security or performance reasons. However, the majoradvantage of the HMAC construct is that it can be proven secure providedthe underlying hash function has some reasonable cryptographicstrengths—that is, HMAC's strengths are directly connected to thestrength of the hash function. Since the HMAC construct is a wrapper,any iterative hash function can be used in an HMAC. Examples includeHMAC-MD5, HMAC-SHA1, HMAC-RIPEMD160 etc. Given the followingdefinitions:

-   -   H=the hash function (e.g. MD5 or SHA-1)    -   n=number of bits output from H (e.g. 160 for SHA-1, 128 bits for        MD5)    -   M=the data to which the MAC function is to be applied    -   K=the secret key shared by the two parties    -   ipad=0x36 repeated 64 times    -   opad=0x5C repeated 64 times

The HMAC algorithm is as follows:

Extend K to 64 bytes by appending 0x00 bytes to the end of KXOR the 64 byte string created in (1) with ipadAppend data stream M to the 64 byte string created in (2)Apply H to the stream generated in (3)XOR the 64 byte string created in (1) with opadAppend the H result from (4) to the 64 byte string resulting from (5)Apply H to the output of (6) and output the result

Thus:

HMAC[M]=H[(K⊕opad)|H[(K⊕ipad)|M]]

The recommended key length is at least n bits, although it should not belonger than 64 bytes (the length of the hashing block). A key longerthan n bits does not add to the security of the function. HMACoptionally allows truncation of the final output e.g. truncation to 128bits from 160 bits. The HMAC designers' Request for Comments was issuedin 1997, one year after the algorithm was first introduced. Thedesigners claimed that the strongest known attack against HMAC is basedon the frequency of collisions for the hash function H and is totallyimpractical for minimally reasonable hash functions. More recently, HMACprotocols with replay prevention components have been defined in orderto prevent the capture and replay of any M, HMAC[M] combination within agiven time period.

Random Numbers and Time Varying Messages

The use of a random number generator as a one-way function has alreadybeen examined. However, random number generator theory is very muchintertwined with cryptography, security, and authentication. There are alarge number of issues concerned with defining good random numbergenerators. Knuth, describes what makes a generator good (includingstatistical tests), and the general problems associated withconstructing them. One of the uses for random numbers is to ensure thatmessages vary over time. Consider a system where A encrypts commands andsends them to B. If the encryption algorithm produces the same outputfor a given input, an attacker could simply record the messages and playthem back to fool B. There is no need for the attacker to crack theencryption mechanism other than to know which message to play to B(while pretending to be A). Consequently messages often include a randomnumber and a time stamp to ensure that the message (and hence itsencrypted counterpart) varies each time. Random number generators arealso often used to generate keys. It is therefore best to say at themoment, that all generators are insecure for this purpose. For example,the Berlekamp-Massey algorithm, is a classic attack on an LFSR randomnumber generator. If the LFSR is of length n, then only 2n bits of thesequence suffice to determine the LFSR, compromising the key generator.If, however, the only role of the random number generator is to makesure that messages vary over time, the security of the generator andseed is not as important as it is for session key generation. Ifhowever, the random number seed generator is compromised, and anattacker is able to calculate future “random” numbers, it can leave someprotocols open to attack. Any new protocol should be examined withrespect to this situation. The actual type of random number generatorrequired will depend upon the implementation and the purposes for whichthe generator is used. Generators include Blum, Blum, and Shub, streamciphers such as RC4 by Ron Rivest, hash functions such as SHA-1 andRIPEMD-160, and traditional generators such LFSRs (Linear Feedback ShiftRegisters) and their more recent counterpart FCSRs (Feedback with CarryShift Registers).

ATTACKS

This section describes the various types of attacks that can beundertaken to break an authentication cryptosystem such as theauthentication chip. The attacks are grouped into physical and logicalattacks. Physical attacks describe methods for breaking a physicalimplementation of a cryptosystem (for example, breaking open a chip toretrieve the key), while logical attacks involve attacks on thecryptosystem that are implementation independent. Logical types ofattack work on the protocols or algorithms, and attempt to do one ofthree things:

-   -   Bypass the authentication process altogether    -   Obtain the secret key by force or deduction, so that any        question can be answered    -   Find enough about the nature of the authenticating questions and        answers in order to, without the key, give the right answer to        each question.

The attack styles and the forms they take are detailed below. Regardlessof the algorithms and protocol used by a security chip, the circuitry ofthe authentication part of the chip can come under physical attack.Physical attack comes in four main ways, although the form of the attackcan vary:

-   -   Bypassing the Authentication Chip altogether    -   Physical examination of chip while in operation (destructive and        non-destructive)    -   Physical decomposition of chip    -   Physical alteration of chip

The attack styles and the forms they take are detailed below. Thissection does not suggest solutions to these attacks. It merely describeseach attack type. The examination is restricted to the context of anAuthentication chip 53 (as opposed to some other kind of system, such asInternet authentication) attached to some System.

Logical Attacks

These attacks are those which do not depend on the physicalimplementation of the cryptosystem. They work against the protocols andthe security of the algorithms and random number generators.

Ciphertext Only Attack

This is where an attacker has one or more encrypted messages, allencrypted using the same algorithm. The aim of the attacker is to obtainthe plaintext messages from the encrypted messages. Ideally, the key canbe recovered so that all messages in the future can also be recovered.

Known Plaintext Attack

This is where an attacker has both the plaintext and the encrypted formof the plaintext. In the case of an Authentication Chip, aknown-plaintext attack is one where the attacker can see the data flowbetween the System and the Authentication Chip. The inputs and outputsare observed (not chosen by the attacker), and can be analyzed forweaknesses (such as birthday attacks or by a search for differentiallyinteresting input/output pairs). A known plaintext attack is a weakertype of attack than the chosen plaintext attack, since the attacker canonly observe the data flow. A known plaintext attack can be carried outby connecting a logic analyzer to the connection between the System andthe Authentication Chip.

Chosen Plaintext Attacks

A chosen plaintext attack describes one where a cryptanalyst has theability to send any chosen message to the cryptosystem, and observe theresponse. If the cryptanalyst knows the algorithm, there may be arelationship between inputs and outputs that can be exploited by feedinga specific output to the input of another function. On a system using anembedded Authentication Chip, it is generally very difficult to preventchosen plaintext attacks since the cryptanalyst can logically pretendhe/she is the System, and thus send any chosen bit-pattern streams tothe Authentication Chip.

Adaptive Chosen Plaintext Attacks

This type of attack is similar to the chosen plaintext attacks exceptthat the attacker has the added ability to modify subsequent chosenplaintexts based upon the results of previous experiments. This iscertainly the case with any System/Authentication Chip scenariodescribed when utilized for consumables such as photocopiers and tonercartridges, especially since both Systems and Consumables are madeavailable to the public.

Brute Force Attack

A guaranteed way to break any key-based cryptosystem algorithm is simplyto try every key. Eventually the right one will be found. This is knownas a Brute Force Attack. However, the more key possibilities there are,the more keys must be tried, and hence the longer it takes (on average)to find the right one. If there are N keys, it will take a maximum of Ntries. If the key is N bits long, it will take a maximum of 2^(N) tries,with a 50% chance of finding the key after only half the attempts(2^(N−1)). The longer N becomes, the longer it will take to find thekey, and hence the more secure the key is. Of course, an attack mayguess the key on the first try, but this is more unlikely the longer thekey is. Consider a key length of 56 bits. In the worst case, all 2⁵⁶tests (7.2×10¹⁶ tests) must be made to find the key. In 1977, Diffie andHellman described a specialized machine for cracking DES, consisting ofone million processors, each capable of running one million tests persecond. Such a machine would take 20 hours to break any DES code.Consider a key length of 128 bits. In the worst case, all 2¹²⁸ tests(3.4×10³⁸ tests) must be made to find the key. This would take tenbillion years on an array of a trillion processors each running 1billion tests per second. With a long enough key length, a Brute ForceAttack takes too long to be worth the attacker's efforts.

Guessing Attack

This type of attack is where an attacker attempts to simply “guess” thekey. As an attack it is identical to the Brute force attack, where theodds of success depend on the length of the key.

Quantum Computer Attack

To break an n-bit key, a quantum computer (NMR, Optical, or Caged Atom)containing n qubits embedded in an appropriate algorithm must be built.The quantum computer effectively exists in 2^(n) simultaneous coherentstates. The trick is to extract the right coherent state without causingany decoherence. To date this has been achieved with a 2 qubit system(which exists in 4 coherent states). It is thought possible to extendthis to 6 qubits (with 64 simultaneous coherent states) within a fewyears.

Unfortunately, every additional qubit halves the relative strength ofthe signal representing the key. This rapidly becomes a seriousimpediment to key retrieval, especially with the long keys used incryptographically secure systems. As a result, attacks on acryptographically secure key (e.g. 160 bits) using a Quantum Computerare likely not to be feasible and it is extremely unlikely that quantumcomputers will have achieved more than 50 or so qubits within thecommercial lifetime of the Authentication Chips. Even using a 50 qubitquantum computer, 2¹¹⁰ tests are required to crack a 160 bit key.

Purposeful Error Attack

With certain algorithms, attackers can gather valuable information fromthe results of a bad input. This can range from the error message textto the time taken for the error to be generated. A simple example isthat of a userid/password scheme. If the error message usually says “Baduserid”, then when an attacker gets a message saying “Bad password”instead, then they know that the userid is correct. If the messagealways says “Bad userid/password” then much less information is given tothe attacker. A more complex example is that of the recent publishedmethod of cracking encryption codes from secure web sites. The attackinvolves sending particular messages to a server and observing the errormessage responses. The responses give enough information to learn thekeys—even the lack of a response gives some information. An example ofalgorithmic time can be seen with an algorithm that returns an error assoon as an erroneous bit is detected in the input message. Depending onhardware implementation, it may be a simple method for the attacker totime the response and alter each bit one by one depending on the timetaken for the error response, and thus obtain the key. Certainly in achip implementation the time taken can be observed with far greateraccuracy than over the Internet.

Birthday Attack

This attack is named after the famous “birthday paradox” (which is notactually a paradox at all). The odds of one person sharing a birthdaywith another, is 1 in 365 (not counting leap years). Therefore theremust be 183 people in a room for the odds to be more than 50% that oneof them shares your birthday. However, there only needs to be 23 peoplein a room for there to be more than a 50% chance that any two share abirthday. This is because 23 people yields 253 different pairs. Birthdayattacks are common attacks against hashing algorithms, especially thosealgorithms that combine hashing with digital signatures. If a messagehas been generated and already signed, an attacker must search for acollision message that hashes to the same value (analogous to findingone person who shares your birthday). However, if the attacker cangenerate the message, the Birthday Attack comes into play. The attackersearches for two messages that share the same hash value (analogous toany two people sharing a birthday), only one message is acceptable tothe person signing it, and the other is beneficial for the attacker.Once the person has signed the original message the attacker simplyclaims now that the person signed the alternative message—mathematicallythere is no way to tell which message was the original, since they bothhash to the same value. Assuming a Brute Force Attack is the only way todetermine a match, the weakening of an n-bit key by the birthday attackis 2^(n/2). A key length of 128 bits that is susceptible to the birthdayattack has an effective length of only 64 bits.

Chaining Attack

These are attacks made against the chaining nature of hash functions.They focus on the compression function of a hash function. The idea isbased on the fact that a hash function generally takes arbitrary lengthinput and produces a constant length output by processing the input nbits at a time. The output from one block is used as the chainingvariable set into the next block. Rather than finding a collisionagainst an entire input, the idea is that given an input chainingvariable set, to find a substitute block that will result in the sameoutput chaining variables as the proper message. The number of choicesfor a particular block is based on the length of the block. If thechaining variable is c bits, the hashing function behaves like a randommapping, and the block length is b bits, the number of such b-bit blocksis approximately 2b/2c. The challenge for finding a substitution blockis that such blocks are a sparse subset of all possible blocks. ForSHA-1, the number of 512 bit blocks is approximately 2⁵¹²/2¹⁶⁰, or 2³⁵².The chance of finding a block by brute force search is about 1 in 2¹⁶⁰.

Substitution with a Complete Lookup Table

If the number of potential messages sent to the chip is small, thenthere is no need for a clone manufacturer to crack the key. Instead, theclone manufacturer could incorporate a ROM in their chip that had arecord of all of the responses from a genuine chip to the codes sent bythe system. The larger the key, and the larger the response, the morespace is required for such a lookup table.

Substitution with a Sparse Lookup Table

If the messages sent to the chip are somehow predictable, rather thaneffectively random, then the clone manufacturer need not provide acomplete lookup table. For example:

-   -   If the message is simply a serial number, the clone manufacturer        need simply provide a lookup table that contains values for past        and predicted future serial numbers. There are unlikely to be        more than 10⁹ of these.    -   If the test code is simply the date, then the clone manufacturer        can produce a lookup table using the date as the address.    -   If the test code is a pseudo-random number using either the        serial number or the date as a seed, then the clone manufacturer        just needs to crack the pseudo-random number generator in the        System. This is probably not difficult, as they have access to        the object code of the System. The clone manufacturer would then        produce a content addressable memory (or other sparse array        lookup) using these codes to access stored authentication codes.

Differential Cryptanalysis

Differential cryptanalysis describes an attack where pairs of inputstreams are generated with known differences, and the differences in theencoded streams are analyzed. Existing differential attacks are heavilydependent on the structure of S boxes, as used in DES and other similaralgorithms. Although other algorithms such as HMAC-SHA1 have no S boxes,an attacker can undertake a differential-like attack by undertakingstatistical analysis of:

-   -   Minimal-difference inputs, and their corresponding outputs    -   Minimal-difference outputs, and their corresponding inputs

Most algorithms were strengthened against differential cryptanalysisonce the process was described. This is covered in the specific sectionsdevoted to each cryptographic algorithm. However some recent algorithmsdeveloped in secret have been broken because the developers had notconsidered certain styles of differential attacks and did not subjecttheir algorithms to public scrutiny.

Message Substitution Attacks

In certain protocols, a man-in-the-middle can substitute part or all ofa message. This is where a real Authentication Chip is plugged into areusable clone chip within the consumable. The clone chip intercepts allmessages between the System and the Authentication Chip, and can performa number of substitution attacks. Consider a message containing a headerfollowed by content. An attacker may not be able to generate a validheader, but may be able to substitute their own content, especially ifthe valid response is something along the lines of “Yes, I received yourmessage”. Even if the return message is “Yes, I received the followingmessage . . . ”, the attacker may be able to substitute the originalmessage before sending the acknowledgement back to the original sender.Message Authentication Codes were developed to combat most messagesubstitution attacks.

Reverse Engineering the Key Generator

If a pseudo-random number generator is used to generate keys, there isthe potential for a clone manufacture to obtain the generator program orto deduce the random seed used. This was the way in which the Netscapesecurity program was initially broken.

Bypassing Authentication Altogether

It may be that there are problems in the authentication protocols thatcan allow a bypass of the authentication process altogether. With thesekinds of attacks the key is completely irrelevant, and the attacker hasno need to recover it or deduce it. Consider an example of a system thatAuthenticates at power-up, but does not authenticate at any other time.A reusable consumable with a clone Authentication Chip may make use of areal Authentication Chip. The clone authentication chip 53 uses the realchip for the authentication call, and then simulates the realAuthentication Chip's state data after that. Another example ofbypassing authentication is if the System authenticates only after theconsumable has been used. A clone Authentication Chip can accomplish asimple authentication bypass by simulating a loss of connection afterthe use of the consumable but before the authentication protocol hascompleted (or even started). One infamous attack known as the “KentuckyFried Chip” hack involved replacing a microcontroller chip for asatellite TV system. When a subscriber stopped paying the subscriptionfee, the system would send out a “disable” message. However the newmicrocontroller would simply detect this message and not pass it on tothe consumer's satellite TV system.

Garrote/Bribe Attack

If people know the key, there is the possibility that they could tellsomeone else. The telling may be due to coercion (bribe, garrote etc),revenge (e.g. a disgruntled employee), or simply for principle. Theseattacks are usually cheaper and easier than other efforts at deducingthe key. As an example, a number of people claiming to be involved withthe development of the Divx standard have recently (May/June 1998) beenmaking noises on a variety of DVD newsgroups to the effect they wouldlike to help develop Divx specific cracking devices—out of principle.

Physical Attacks

The following attacks assume implementation of an authenticationmechanism in a silicon chip that the attacker has physical access to.The first attack, Reading ROM, describes an attack when keys are storedin ROM, while the remaining attacks assume that a secret key is storedin Flash memory.

Reading ROM

If a key is stored in ROM it can be read directly. A ROM can thus besafely used to hold a public key (for use in asymmetric cryptography),but not to hold a private key. In symmetric cryptography, a ROM iscompletely insecure. Using a copyright text (such as a haiku) as the keyis not sufficient, because we are assuming that the cloning of the chipis occurring in a country where intellectual property is not respected.

Reverse Engineering of Chip

Reverse engineering of the chip is where an attacker opens the chip andanalyzes the circuitry. Once the circuitry has been analyzed the innerworkings of the chip's algorithm can be recovered. Lucent Technologieshave developed an active method known as TOBIC (Two photon OBIC, whereOBIC stands for Optical Beam Induced Current), to image circuits.Developed primarily for static RAM analysis, the process involvesremoving any back materials, polishing the back surface to a mirrorfinish, and then focusing light on the surface. The excitationwavelength is specifically chosen not to induce a current in the IC. AKerckhoffs in the nineteenth century made a fundamental assumption aboutcryptanalysis: if the algorithm's inner workings are the sole secret ofthe scheme, the scheme is as good as broken. He stipulated that thesecrecy must reside entirely in the key. As a result, the best way toprotect against reverse engineering of the chip is to make the innerworkings irrelevant.

Usurping the Authentication Process

It must be assumed that any clone manufacturer has access to both theSystem and consumable designs. If the same channel is used forcommunication between the System and a trusted System AuthenticationChip, and a non-trusted consumable Authentication Chip, it may bepossible for the non-trusted chip to interrogate a trustedAuthentication Chip in order to obtain the “correct answer”. If this isso, a clone manufacturer would not have to determine the key. They wouldonly have to trick the System into using the responses from the SystemAuthentication Chip. The alternative method of usurping theauthentication process follows the same method as the logical attack“Bypassing the Authentication Process”, involving simulated loss ofcontact with the System whenever authentication processes take place,simulating power-down etc.

Modification of System

This kind of attack is where the System itself is modified to acceptclone consumables. The attack may be a change of System ROM, a rewiringof the consumable, or, taken to the extreme case, a completely cloneSystem. This kind of attack requires each individual System to bemodified, and would most likely require the owner's consent. There wouldusually have to be a clear advantage for the consumer to undertake sucha modification, since it would typically void warranty and would mostlikely be costly. An example of such a modification with a clearadvantage to the consumer is a software patch to change fixed-region DVDplayers into region-free DVD players.

Direct Viewing of Chip Operation by Conventional Probing

If chip operation could be directly viewed using an STM or an electronbeam, the keys could be recorded as they are read from the internalnon-volatile memory and loaded into work registers. These forms ofconventional probing require direct access to the top or front sides ofthe IC while it is powered.

Direct Viewing of the Non-Volatile Memory

If the chip were sliced so that the floating gates of the Flash memorywere exposed, without discharging them, then the key could probably beviewed directly using an STM or SKM (Scanning Kelvin Microscope).However, slicing the chip to this level without discharging the gates isprobably impossible. Using wet etching, plasma etching, ion milling(focused ion beam etching), or chemical mechanical polishing will almostcertainly discharge the small charges present on the floating gates.

Viewing the Light Bursts Caused by State Changes

Whenever a gate changes state, a small amount of infrared energy isemitted. Since silicon is transparent to infrared, these changes can beobserved by looking at the circuitry from the underside of a chip. Whilethe emission process is weak, it is bright enough to be detected byhighly sensitive equipment developed for use in astronomy. Thetechnique, developed by IBM, is called PICA (Picosecond Imaging CircuitAnalyzer). If the state of a register is known at time t, then watchingthat register change over time will reveal the exact value at time t+n,and if the data is part of the key, then that part is compromised.

Monitoring EMI

Whenever electronic circuitry operates, faint electromagnetic signalsare given off. Relatively inexpensive equipment (a few thousand dollars)can monitor these signals. This could give enough information to allowan attacker to deduce the keys.

Viewing I_(dd) Fluctuations

Even if keys cannot be viewed, there is a fluctuation in currentwhenever registers change state. If there is a high enough signal tonoise ratio, an attacker can monitor the difference in I_(dd) that mayoccur when programming over either a high or a low bit. The change inI_(dd) can reveal information about the key. Attacks such as these havealready been used to break smart cards.

Differential Fault Analysis

This attack assumes introduction of a bit error by ionization, microwaveradiation, or environmental stress. In most cases such an error is morelikely to adversely affect the Chip (eg cause the program code to crash)rather than cause beneficial changes which would reveal the key.Targeted faults such as ROM overwrite, gate destruction etc are far morelikely to produce useful results.

Clock Glitch Attacks

Chips are typically designed to properly operate within a certain clockspeed range. Some attackers attempt to introduce faults in logic byrunning the chip at extremely high clock speeds or introduce a clockglitch at a particular time for a particular duration. The idea is tocreate race conditions where the circuitry does not function properly.An example could be an AND gate that (because of race conditions) gatesthrough Input₁ all the time instead of the AND of Input₁ and Input₂. Ifan attacker knows the internal structure of the chip, they can attemptto introduce race conditions at the correct moment in the algorithmexecution, thereby revealing information about the key (or in the worstcase, the key itself).

Power Supply Attacks

Instead of creating a glitch in the clock signal, attackers can alsoproduce glitches in the power supply where the power is increased ordecreased to be outside the working operating voltage range. The neteffect is the same as a clock glitch—introduction of error in theexecution of a particular instruction. The idea is to stop the CPU fromXORing the key, or from shifting the data one bit-position etc. Specificinstructions are targeted so that information about the key is revealed.

Overwriting ROM

Single bits in a ROM can be overwritten using a laser cutter microscope,to either 1 or 0 depending on the sense of the logic. With a givenopcode/operand set, it may be a simple matter for an attacker to changea conditional jump to a non-conditional jump, or perhaps change thedestination of a register transfer. If the target instruction is chosencarefully, it may result in the key being revealed.

Modifying EEPROM/Flash EEPROM/Flash attacks are similar to ROM attacksexcept that the laser cutter microscope technique can be used to bothset and reset individual bits. This gives much greater scope in terms ofmodification of algorithms.

Gate Destruction

Anderson and Kuhn described the rump session of the 1997 workshop onFast Software Encryption, where Biham and Shamir presented an attack onDES. The attack was to use a laser cutter to destroy an individual gatein the hardware implementation of a known block cipher (DES). The neteffect of the attack was to force a particular bit of a register to be“stuck”. Biham and Shamir described the effect of forcing a particularregister to be affected in this way—the least significant bit of theoutput from the round function is set to 0. Comparing the 6 leastsignificant bits of the left half and the right half can recover severalbits of the key. Damaging a number of chips in this way can revealenough information about the key to make complete key recovery easy. Anencryption chip modified in this way will have the property thatencryption and decryption will no longer be inverses.

Overwrite Attacks

Instead of trying to read the Flash memory, an attacker may simply set asingle bit by use of a laser cutter microscope. Although the attackerdoesn't know the previous value, they know the new value. If the chipstill works, the bit's original state must be the same as the new state.If the chip doesn't work any longer, the bit's original state must bethe logical NOT of the current state. An attacker can perform thisattack on each bit of the key and obtain the n-bit key using at most nchips (if the new bit matched the old bit, a new chip is not requiredfor determining the next bit).

Test Circuitry Attack

Most chips contain test circuitry specifically designed to check formanufacturing defects. This includes BIST (Built In Self Test) and scanpaths. Quite often the scan paths and test circuitry includes access andreadout mechanisms for all the embedded latches. In some cases the testcircuitry could potentially be used to give information about thecontents of particular registers. Test circuitry is often disabled oncethe chip has passed all manufacturing tests, in some cases by blowing aspecific connection within the chip. A determined attacker, however, canreconnect the test circuitry and hence enable it.

Memory Remanence

Values remain in RAM long after the power has been removed, althoughthey do not remain long enough to be considered non-volatile. Anattacker can remove power once sensitive information has been moved intoRAM (for example working registers), and then attempt to read the valuefrom RAM. This attack is most useful against security systems that haveregular RAM chips. A classic example is where a security system wasdesigned with an automatic power-shut-off that is triggered when thecomputer case is opened. The attacker was able to simply open the case,remove the RAM chips, and retrieve the key because of memory remanence.

Chip Theft Attack

If there are a number of stages in the lifetime of an AuthenticationChip, each of these stages must be examined in terms of ramificationsfor security should chips be stolen. For example, if information isprogrammed into the chip in stages, theft of a chip between stages mayallow an attacker to have access to key information or reduced effortsfor attack. Similarly, if a chip is stolen directly after manufacturebut before programming, does it give an attacker any logical or physicaladvantage?

Requirements

Existing solutions to the problem of authenticating consumables havetypically relied on physical patents on packaging. However this does notstop home refill operations or clone manufacture in countries with weakindustrial property protection. Consequently a much higher level ofprotection is required. The authentication mechanism is therefore builtinto an Authentication chip 53 that allows a system to authenticate aconsumable securely and easily. Limiting ourselves to the systemauthenticating consumables (we don't consider the consumableauthenticating the system), two levels of protection can be considered:

Presence Only Authentication

This is where only the presence of an Authentication Chip is tested. TheAuthentication Chip can be reused in another consumable without beingreprogrammed.

Consumable Lifetime Authentication

This is where not only is the presence of the Authentication Chip testedfor, but also the Authentication chip 53 must only last the lifetime ofthe consumable. For the chip to be reused it must be completely erasedand reprogrammed. The two levels of protection address differentrequirements. We are primarily concerned with Consumable LifetimeAuthentication in order to prevent cloned versions of high volumeconsumables. In this case, each chip should hold secure stateinformation about the consumable being authenticated. It should be notedthat a Consumable Lifetime Authentication Chip could be used in anysituation requiring a Presence Only Authentication Chip. Therequirements for authentication, data storage integrity and manufactureshould be considered separately. The following sections summarizerequirements of each.

Authentication

The authentication requirements for both Presence Only Authenticationand Consumable Lifetime Authentication are restricted to case of asystem authenticating a consumable. For Presence Only Authentication, wemust be assured that an Authentication Chip is physically present. ForConsumable Lifetime Authentication we also need to be assured that statedata actually came from the Authentication Chip, and that it has notbeen altered en route. These issues cannot be separated—data that hasbeen altered has a new source, and if the source cannot be determined,the question of alteration cannot be settled. It is not enough toprovide an authentication method that is secret, relying on a home-brewsecurity method that has not been scrutinized by security experts. Theprimary requirement therefore is to provide authentication by means thathave withstood the scrutiny of experts. The authentication scheme usedby the Authentication chip 53 should be resistant to defeat by logicalmeans. Logical types of attack are extensive, and attempt to do one ofthree things:

-   -   Bypass the authentication process altogether    -   Obtain the secret key by force or deduction, so that any        question can be answered    -   Find enough about the nature of the authenticating questions and        answers in order to, without the key, give the right answer to        each question.

Data Storage Integrity

Although Authentication protocols take care of ensuring data integrityin communicated messages, data storage integrity is also required. Twokinds of data must be stored within the Authentication Chip:

-   -   Authentication data, such as secret keys    -   Consumable state data, such as serial numbers, and media        remaining etc.

The access requirements of these two data types differ greatly. TheAuthentication chip 53 therefore requires a storage/access controlmechanism that allows for the integrity requirements of each type.

Authentication Data

Authentication data must remain confidential. It needs to be stored inthe chip during a manufacturing/programming stage of the chip's life,but from then on must not be permitted to leave the chip. It must beresistant to being read from non-volatile memory. The authenticationscheme is responsible for ensuring the key cannot be obtained bydeduction, and the manufacturing process is responsible for ensuringthat the key cannot be obtained by physical means. The size of theauthentication data memory area must be large enough to hold thenecessary keys and secret information as mandated by the authenticationprotocols.

Consumable State Data

Each Authentication chip 53 needs to be able to also store 256 bits (32bytes) of consumable state data. Consumable state data can be dividedinto the following types. Depending on the application, there will bedifferent numbers of each of these types of data items. A maximum numberof 32 bits for a single data item is to be considered.

-   -   Read Only    -   ReadWrite    -   Decrement Only

Read Only data needs to be stored in the chip during amanufacturing/programming stage of the chip's life, but from then onshould not be allowed to change. Examples of Read Only data items areconsumable batch numbers and serial numbers.

ReadWrite data is changeable state information, for example, the lasttime the particular consumable was used. ReadWrite data items can beread and written an unlimited number of times during the lifetime of theconsumable. They can be used to store any state information about theconsumable. The only requirement for this data is that it needs to bekept in non-volatile memory. Since an attacker can obtain access to asystem (which can write to ReadWrite data), any attacker can potentiallychange data fields of this type. This data type should not be used forsecret information, and must be considered insecure.

Decrement Only data is used to count down the availability of consumableresources. A photocopier's toner cartridge, for example, may store theamount of toner remaining as a Decrement Only data item. An inkcartridge for a color printer may store the amount of each ink color asa Decrement Only data item, requiring 3 (one for each of Cyan, Magenta,and Yellow), or even as many as 5 or 6 Decrement Only data items. Therequirement for this kind of data item is that once programmed with aninitial value at the manufacturing/programming stage, it can only reducein value. Once it reaches the minimum value, it cannot decrement anyfurther. The Decrement Only data item is only required by ConsumableLifetime Authentication.

Manufacture

The Authentication chip 53 ideally must have a low manufacturing cost inorder to be included as the authentication mechanism for low costconsumables. The Authentication chip 53 should use a standardmanufacturing process, such as Flash. This is necessary to:

-   -   Allow a great range of manufacturing location options    -   Use well-defined and well-behaved technology    -   Reduce cost

Regardless of the authentication scheme used, the circuitry of theauthentication part of the chip must be resistant to physical attack.Physical attack comes in four main ways, although the form of the attackcan vary:

-   -   Bypassing the Authentication Chip altogether    -   Physical examination of chip while in operation (destructive and        non-destructive)    -   Physical decomposition of chip    -   Physical alteration of chip

Ideally, the chip should be exportable from the U.S., so it should notbe possible to use an Authentication chip 53 as a secure encryptiondevice. This is low priority requirement since there are many companiesin other countries able to manufacture the Authentication chips. In anycase, the export restrictions from the U.S. may change.

Authentication

Existing solutions to the problem of authenticating consumables havetypically relied on physical patents on packaging. However this does notstop home refill operations or clone manufacture in countries with weakindustrial property protection. Consequently a much higher level ofprotection is required. It is not enough to provide an authenticationmethod that is secret, relying on a home-brew security method that hasnot been scrutinized by security experts. Security systems such asNetscape's original proprietary system and the GSM Fraud PreventionNetwork used by cellular phones are examples where design secrecy causedthe vulnerability of the security. Both security systems were broken byconventional means that would have been detected if the companies hadfollowed an open design process. The solution is to provideauthentication by means that have withstood the scrutiny of experts. Anumber of protocols that can be used for consumables authentication. Weonly use security methods that are publicly described, using knownbehaviors in this new way. For all protocols, the security of the schemerelies on a secret key, not a secret algorithm. All the protocols relyon a time-variant challenge (i.e. the challenge is different each time),where the response depends on the challenge and the secret. Thechallenge involves a random number so that any observer will not be ableto gather useful information about a subsequent identification. Twoprotocols are presented for each of Presence Only Authentication andConsumable Lifetime Authentication. Although the protocols differ in thenumber of Authentication Chips required for the authentication process,in all cases the System authenticates the consumable. Certain protocolswill work with either one or two chips, while other protocols only workwith two chips. Whether one chip or two Authentication Chips are usedthe System is still responsible for making the authentication decision.

Single Chip Authentication

When only one Authentication chip 53 is used for the authenticationprotocol, a single chip (referred to as ChipA) is responsible forproving to a system (referred to as System) that it is authentic. At thestart of the protocol, System is unsure of ChipA's authenticity. Systemundertakes a challenge-response protocol with ChipA, and thus determinesChipA's authenticity. In all protocols the authenticity of theconsumable is directly based on the authenticity of the chip, i.e. ifChipA is considered authentic, then the consumable is consideredauthentic. The data flow can be seen in FIG. 167. In single chipauthentication protocols, System can be software, hardware or acombination of both. It is important to note that System is consideredinsecure—it can be easily reverse engineered by an attacker, either byexamining the ROM or by examining circuitry. System is not speciallyengineered to be secure in itself.

Double Chip Authentication

In other protocols, two Authentication Chips are required as shown inFIG. 168. A single chip (referred to as ChipA) is responsible forproving to a system (referred to as System) that it is authentic. Aspart of the authentication process, System makes use of a trustedAuthentication Chip (referred to as ChipT). In double chipauthentication protocols, System can be software, hardware or acombination of both. However ChipT must be a physical AuthenticationChip. In some protocols ChipT and ChipA have the same internalstructure, while in others ChipT and ChipA have different internalstructures.

Presence Only Authentication (Insecure State Data)

For this level of consumable authentication we are only concerned aboutvalidating the presence of the Authentication chip 53. Although theAuthentication Chip can contain state information, the transmission ofthat state information would not be considered secure. Two protocols arepresented. Protocol 1 requires 2 Authentication Chips, while Protocol 2can be implemented using either 1 or 2 Authentication Chips.

Protocol 1

Protocol 1 is a double chip protocol (two Authentication Chips arerequired). Each Authentication Chip contains the following values:

-   -   K Key for F_(K)[X]. Must be secret.    -   R Current random number. Does not have to be secret, but must be        seeded with a different initial value for each chip instance.        Changes with each invocation of the Random function.

Each Authentication Chip contains the following logical functions:

-   -   Random[ ] Returns R, and advances R to next in sequence.    -   F[X] Returns F_(K)[X], the result of applying a one-way function        F to X based upon the secret key K.

The protocol is as follows:

-   -   System requests Random[ ] from ChipT;    -   ChipT returns R to System;    -   System requests F[R] from both ChipT and ChipA;    -   ChipT returns F_(KT)[R] to System;    -   ChipA returns F_(KT)[R] to System;    -   System compares F_(KT)[R] with F_(KT)[R]. If they are equal,        then ChipA is considered valid. If not, then ChipA is considered        invalid.

The data flow can be seen in FIG. 169. The System does not have tocomprehend F_(K)[R] messages. It must merely check that the responsesfrom ChipA and ChipT are the same. The System therefore does not requirethe key. The security of Protocol 1 lies in two places:

-   -   The security of F[X]. Only Authentication chips contain the        secret key, so anything that can produce an F[X] from an X that        matches the F[X] generated by a trusted Authentication chip 53        (ChipT) must be authentic.    -   The domain of R generated by all Authentication chips must be        large and non-deterministic. If the domain of R generated by all        Authentication chips is small, then there is no need for a clone        manufacturer to crack the key. Instead, the clone manufacturer        could incorporate a ROM in their chip that had a record of all        of the responses from a genuine chip to the codes sent by the        system. The Random function does not strictly have to be in the        Authentication Chip, since System can potentially generate the        same random number sequence. However it simplifies the design of        System and ensures the security of the random number generator        will be the same for all implementations that use the        Authentication Chip, reducing possible error in system        implementation.

Protocol 1 has several advantages:

-   -   K is not revealed during the authentication process    -   Given X, a clone chip cannot generate F_(K)[X] without K or        access to a real Authentication Chip.    -   System is easy to design, especially in low cost systems such as        ink-jet printers, as no encryption or decryption is required by        System itself.    -   A wide range of keyed one-way functions exists, including        symmetric cryptography, random number sequences, and message        authentication codes.    -   One-way functions require fewer gates and are easier to verify        than asymmetric algorithms).    -   Secure key size for a keyed one-way function does not have to be        as large as for an asymmetric (public key) algorithm. A minimum        of 128 bits can provide appropriate security if F[X] is a        symmetric cryptographic function.

However there are problems with this protocol:

-   -   It is susceptible to chosen text attack. An attacker can plug        the chip into their own system, generate chosen Rs, and observe        the output. In order to find the key, an attacker can also        search for an R that will generate a specific F[M] since        multiple Authentication chips can be tested in parallel.    -   Depending on the one-way function chosen, key generation can be        complicated. The method of selecting a good key depends on the        algorithm being used. Certain keys are weak for a given        algorithm.    -   The choice of the keyed one-way functions itself is non-trivial.        Some require licensing due to patent protection.

A man-in-the middle could take action on a plaintext message M beforepassing it on to ChipA—it would be preferable if the man-in-the-middledid not see M until after ChipA had seen it. It would be even morepreferable if a man-in-the-middle didn't see M at all.

If F is symmetric encryption, because of the key size needed foradequate security, the chips could not be exported from the USA sincethey could be used as strong encryption devices.

If Protocol 1 is implemented with F as an asymmetric encryptionalgorithm, there is no advantage over the symmetric case—the keys needsto be longer and the encryption algorithm is more expensive in silicon.Protocol 1 must be implemented with 2 Authentication Chips in order tokeep the key secure. This means that each System requires anAuthentication Chip and each consumable requires an Authentication Chip.

Protocol 2

In some cases, System may contain a large amount of processing power.Alternatively, for instances of systems that are manufactured in largequantities, integration of ChipT into System may be desirable. Use of anasymmetrical encryption algorithm allows the ChipT portion of System tobe insecure. Protocol 2 therefore, uses asymmetric cryptography. Forthis protocol, each chip contains the following values:

-   -   K Key for E_(K)[X] and D_(K)[X]. Must be secret in ChipA. Does        not have to be secret in ChipT.    -   R Current random number. Does not have to be secret, but must be        seeded with a different initial value for each chip instance.        Changes with each invocation of the Random function.

The following functions are defined:

-   -   E[X] ChipT only. Returns E_(K)[X] where E is asymmetric encrypt        function E.    -   D[X] ChipA only. Returns D_(K)[X] where D is asymmetric decrypt        function D.    -   Random[ ] ChipT only. Returns R|E_(K)[R], where R is random        number based on seed S. Advances R to next in random number        sequence.

The public key K_(T) is in ChipT, while the secret key K_(A) is inChipA. Having K_(T) in ChipT has the advantage that ChipT can beimplemented in software or hardware (with the proviso that the seed forR is different for each chip or system). Protocol 2 therefore can beimplemented as a Single Chip Protocol or as a Double Chip Protocol. Theprotocol for authentication is as follows:

-   -   System calls ChipT's Random function;    -   ChipT returns R|E_(KT)[R] to System;    -   System calls ChipA's D function, passing in E_(KT)[R];    -   ChipA returns R, obtained by D_(KA)[E_(KT)[R]];    -   System compares R from ChipA to the original R generated by        ChipT. If they are equal, then ChipA is considered valid. If        not, ChipA is invalid.

The data flow can be seen in FIG. 170. Protocol 2 has the followingadvantages:

-   -   K_(A) (the secret key) is not revealed during the authentication        process    -   Given E_(KT)[X], a clone chip cannot generate X without K_(A) or        access to a real ChipA.    -   Since K_(T)≠K_(A), ChipT can be implemented completely in        software or in insecure hardware or as part of System. Only        ChipA (in the consumable) is required to be a secure        Authentication Chip.    -   If ChipT is a physical chip, System is easy to design.    -   There are a number of well-documented and cryptanalyzed        asymmetric algorithms to chose from for implementation,        including patent-free and license-free solutions.

However, Protocol 2 has a number of its own problems:

-   -   For satisfactory security, each key needs to be 2048 bits        (compared to minimum 128 bits for symmetric cryptography in        Protocol 1). The associated intermediate memory used by the        encryption and decryption algorithms is correspondingly larger.    -   Key generation is non-trivial. Random numbers are not good keys.    -   If ChipT is implemented as a core, there may be difficulties in        linking it into a given System ASIC.    -   If ChipT is implemented as software, not only is the        implementation of System open to programming error and        non-rigorous testing, but the integrity of the compiler and        mathematics primitives must be rigorously checked for each        implementation of System. This is more complicated and costly        than simply using a well-tested chip.    -   Although many symmetric algorithms are specifically strengthened        to be resistant to differential cryptanalysis (which is based on        chosen text attacks), the private key K_(A) is susceptible to a        chosen text attack    -   If ChipA and ChipT are instances of the same Authentication        Chip, each chip must contain both asymmetric encrypt and decrypt        functionality. Consequently each chip is larger, more complex,        and more expensive than the chip required for Protocol 1.    -   If the Authentication Chip is broken into 2 chips to save cost        and reduce complexity of design/test, two chips still need to be        manufactured, reducing the economies of scale. This is offset by        the relative numbers of systems to consumables, but must still        be taken into account.    -   Protocol 2 Authentication Chips could not be exported from the        USA, since they would be considered strong encryption devices.

Even if the process of choosing a key for Protocol 2 wasstraightforward, Protocol 2 is impractical at the present time due tothe high cost of silicon implementation (both key size and functionalimplementation). Therefore Protocol 1 is the protocol of choice forPresence Only Authentication.

Clone Consumable Using Real Authentication Chip

Protocols 1 and 2 only check that ChipA is a real Authentication Chip.They do not check to see if the consumable itself is valid. Thefundamental assumption for authentication is that if ChipA is valid, theconsumable is valid. It is therefore possible for a clone manufacturerto insert a real Authentication Chip into a clone consumable. There aretwo cases to consider:

-   -   In cases where state data is not written to the Authentication        Chip, the chip is completely reusable. Clone manufacturers could        therefore recycle a valid consumable into a clone consumable.        This may be made more difficult by melding the Authentication        Chip into the consumable's physical packaging, but it would not        stop refill operators.    -   In cases where state data is written to the Authentication Chip,        the chip may be new, partially used up, or completely used up.        However this does not stop a clone manufacturer from using the        Piggyback attack, where the clone manufacturer builds a chip        that has a real Authentication Chip as a piggyback. The        Attacker's chip (ChipE) is therefore a man-in-the-middle. At        power up, ChipE reads all the memory state values from the real        Authentication chip 53 into its own memory. ChipE then examines        requests from System, and takes different actions depending on        the request. Authentication requests can be passed directly to        the real Authentication chip 53, while read/write requests can        be simulated by a memory that resembles real Authentication Chip        behavior. In this way the Authentication chip 53 will always        appear fresh at power-up. ChipE can do this because the data        access is not authenticated.

In order to fool System into thinking its data accesses were successful,ChipE still requires a real Authentication Chip, and in the second case,a clone chip is required in addition to a real Authentication Chip.Consequently Protocols 1 and 2 can be useful in situations where it isnot cost effective for a clone manufacturer to embed a realAuthentication chip 53 into the consumable. If the consumable cannot berecycled or refilled easily, it may be protection enough to useProtocols 1 or 2. For a clone operation to be successful each cloneconsumable must include a valid Authentication Chip. The chips wouldhave to be stolen en masse, or taken from old consumables. The quantityof these reclaimed chips (as well as the effort in reclaiming them)should not be enough to base a business on, so the added protection ofsecure data transfer (see Protocols 3 and 4) may not be useful.

Longevity of Key

A general problem of these two protocols is that once the authenticationkey is chosen, it cannot easily be changed. In some instances akey-compromise is not a problem, while for others a key compromise isdisastrous. For example, in a car/car-key System/Consumable scenario,the customer has only one set of car/car-keys. Each car has a differentauthentication key. Consequently the loss of a car-key only compromisesthe individual car. If the owner considers this a problem, they must geta new lock on the car by replacing the System chip inside the car'selectronics. The owner's keys must be reprogrammed/replaced to work withthe new car System Authentication Chip. By contrast, a compromise of akey for a high volume consumable market (for example ink cartridges inprinters) would allow a clone ink cartridge manufacturer to make theirown Authentication Chips. The only solution for existing systems is toupdate the System Authentication Chips, which is a costly andlogistically difficult exercise. In any case, consumers' Systems alreadywork—they have no incentive to hobble their existing equipment.

Consumable Lifetime Authentication

In this level of consumable authentication we are concerned withvalidating the existence of the Authentication Chip, as well as ensuringthat the Authentication Chip lasts only as long as the consumable. Inaddition to validating that an Authentication Chip is present, writesand reads of the Authentication Chip's memory space must beauthenticated as well. In this section we assume that the AuthenticationChip's data storage integrity is secure—certain parts of memory are ReadOnly, others are Read/Write, while others are Decrement Only (see thechapter entitled Data Storage Integrity for more information). Twoprotocols are presented. Protocol 3 requires 2 Authentication Chips,while Protocol 4 can be implemented using either 1 or 2 AuthenticationChips.

Protocol 3

This protocol is a double chip protocol (two Authentication Chips arerequired). For this protocol, each Authentication Chip contains thefollowing values:

-   -   K₁ Key for calculating F_(K1)[X]. Must be secret.    -   K₂ Key for calculating F_(K2)[X]. Must be secret.    -   R Current random number. Does not have to be secret, but must be        seeded with a different initial value for each chip instance.        Changes with each successful authentication as defined by the        Test function.    -   M Memory vector of Authentication chip 53. Part of this space        should be different for each chip (does not have to be a random        number).

Each Authentication Chip contains the following logical functions:

-   -   F[X] Internal function only. Returns F_(K)[X], the result of        applying a one-way function F to X based upon either key K₁ or        key K₂    -   Random[ ] Returns R|F_(K1)[R].    -   Test[X, Y] Returns 1 and advances R if F_(K2)[R|X]=Y. Otherwise        returns 0. The time taken to return 0 must be identical for all        bad inputs.    -   Read[X, Y] Returns M|F_(K2)[X|M] if F_(K1)[X]=Y. Otherwise        returns 0. The time taken to return 0 must be identical for all        bad inputs.    -   Write[X] Writes X over those parts of M that can legitimately be        written over.

To authenticate ChipA and read ChipA's memory M:

-   -   System calls ChipT's Random function;    -   ChipT produces R|F_(K)[R] and returns these to System;    -   System calls ChipA's Read function, passing in R, F_(K)[R];    -   ChipA returns M and F_(K)[R|M];    -   System calls ChipT's Test function, passing in M and F_(K)[R|M];    -   System checks response from ChipT. If the response is 1, then        ChipA is considered authentic. If 0, ChipA is considered        invalid.

To authenticate a write of M_(new) to ChipA's memory M:

-   -   System calls ChipA's Write function, passing in M_(new);    -   The authentication procedure for a Read is carried out;    -   If ChipA is authentic and M_(new)=M, the write succeeded.        Otherwise it failed.

The data flow for read authentication is shown in FIG. 171. The firstthing to note about Protocol 3 is that F_(K)[X] cannot be calleddirectly. Instead F_(K)[X] is called indirectly by Random, Test andRead:

-   -   Random[ ] calls F_(K1)[X] X is not chosen by the caller. It is        chosen by the Random function. An attacker must perform a brute        force search using multiple calls to Random, Read, and Test to        obtain a desired X, F_(K1)[X] pair.    -   Test[X,Y] calls F_(K2)[R|X] Does not return result directly, but        compares the result to Y and then returns 1 or 0. Any attempt to        deduce K₂ by calling Test multiple times trying different values        of F_(K2)[R|X] for a given X is reduced to a brute force search        where R cannot even be chosen by the attacker.    -   Read[X, Y] calls F_(K1)[X] X and F_(K1)[X] must be supplied by        caller, so the caller must already know the X, F_(K1)[X] pair.        Since the call returns 0 if Y≠F_(K1)[X], a caller can use the        Read function for a brute force attack on K₁.    -   Read[X, Y] calls F_(K2)[X|M], X is supplied by caller, however X        can only be those values already given out by the Random        function (since X and Y are validated via K₁). Thus a chosen        text attack must first collect pairs from Random (effectively a        brute force attack). In addition, only part of M can be used in        a chosen text attack since some of M is constant (read-only) and        the decrement-only part of M can only be used once per        consumable. In the next consumable the read-only part of M will        be different.

Having F_(K)[X] being called indirectly prevents chosen text attacks onthe Authentication Chip. Since an attacker can only obtain a chosen R,F_(K1)[R] pair by calling Random, Read, and Test multiple times untilthe desired R appears, a brute force attack on K₁ is required in orderto perform a limited chosen text attack on K₂. Any attempt at a chosentext attack on K₂ would be limited since the text cannot be completelychosen: parts of M are read-only, yet different for each AuthenticationChip. The second thing to note is that two keys are used. Given thesmall size of M, two different keys K₁ and K₂ are used in order toensure there is no correlation between F[R] and F[R|M]. K₁ is thereforeused to help protect K₂ against differential attacks. It is not enoughto use a single longer key since M is only 256 bits, and only part of Mchanges during the lifetime of the consumable. Otherwise it ispotentially possible that an attacker via some as-yet undiscoveredtechnique, could determine the effect of the limited changes in M toparticular bit combinations in R and thus calculate F_(K2)[X|M] based onF_(K1)[X]. As an added precaution, the Random and Test functions inChipA should be disabled so that in order to generate R, F_(K)[R] pairs,an attacker must use instances of ChipT, each of which is more expensivethan ChipA (since a system must be obtained for each ChipT). Similarly,there should be a minimum delay between calls to Random, Read and Testso that an attacker cannot call these functions at high speed. Thus eachchip can only give a specific number of X, F_(K)[X] pairs away in acertain time period. The only specific timing requirement of Protocol 3is that the return value of 0 (indicating a bad input) must be producedin the same amount of time regardless of where the error is in theinput. Attackers can therefore not learn anything about what was badabout the input value. This is true for both RD and TST functions.

Another thing to note about Protocol 3 is that Reading data from ChipAalso requires authentication of ChipA. The System can be sure that thecontents of memory (M) is what ChipA claims it to be if F_(K2)[R|M] isreturned correctly. A clone chip may pretend that M is a certain value(for example it may pretend that the consumable is full), but it cannotreturn F_(K2)[R|M] for any R passed in by System. Thus the effectivesignature F_(K2)[R|M] assures System that not only did an authenticChipA send M, but also that M was not altered in between ChipA andSystem. Finally, the Write function as defined does not authenticate theWrite. To authenticate a write, the System must perform a Read aftereach Write. There are some basic advantages with Protocol 3:

-   -   K₁ and K₂ are not revealed during the authentication process    -   Given X, a clone chip cannot generate F_(K2)[X|M] without the        key or access to a real Authentication Chip.    -   System is easy to design, especially in low cost systems such as        ink-jet printers, as no encryption or decryption is required by        System itself.    -   A wide range of key based one-way functions exists, including        symmetric cryptography, random number sequences, and message        authentication codes.    -   Keyed one-way functions require fewer gates and are easier to        verify than asymmetric algorithms).    -   Secure key size for a keyed one-way function does not have to be        as large as for an asymmetric (public key) algorithm. A minimum        of 128 bits can provide appropriate security if F[X] is a        symmetric cryptographic function.

Consequently, with Protocol 3, the only way to authenticate ChipA is toread the contents of ChipA's memory. The security of this protocoldepends on the underlying F_(K)[X] scheme and the domain of R over theset of all Systems. Although F_(K)[X] can be any keyed one-way function,there is no advantage to implement it as asymmetric encryption. The keysneed to be longer and the encryption algorithm is more expensive insilicon. This leads to a second protocol for use with asymmetricalgorithms—Protocol 4. Protocol 3 must be implemented with 2Authentication Chips in order to keep the keys secure. This means thateach System requires an Authentication Chip and each consumable requiresan Authentication Chip

Protocol 4

In some cases, System may contain a large amount of processing power.Alternatively, for instances of systems that are manufactured in largequantities, integration of ChipT into System may be desirable. Use of anasymmetrical encryption algorithm can allow the ChipT portion of Systemto be insecure. Protocol 4 therefore, uses asymmetric cryptography. Forthis protocol, each chip contains the following values:

-   -   K Key for E_(K)[X] and D_(K)[X]. Must be secret in ChipA. Does        not have to be secret in ChipT.    -   R Current random number. Does not have to be secret, but must be        seeded with a different initial value for each chip instance.        Changes with each successful authentication as defined by the        Test function.    -   M Memory vector of Authentication chip 53. Part of this space        should be different for each chip, (does not have to be a random        number).

There is no point in verifying anything in the Read function, sinceanyone can encrypt using a public key. Consequently the followingfunctions are defined:

-   -   E[X] Internal function only. Returns E_(K)[X] where E is        asymmetric encrypt function E.    -   D[X] Internal function only. Returns D_(K)[X] where D is        asymmetric decrypt function D.    -   Random[ ] ChipT only. Returns E_(K)[R].    -   Test[X, Y] Returns 1 and advances R if D_(K)[R|X]=Y. Otherwise        returns 0. The time taken to return 0 must be identical for all        bad inputs.    -   Read[X] Returns M|E_(K)[R|M] where R=D_(K)[X] (does not test        input).    -   Write[X] Writes X over those parts of M that can legitimately be        written over.

The public key K_(T) is in ChipT, while the secret key K_(A) is inChipA. Having K_(T) in ChipT has the advantage that ChipT can beimplemented in software or hardware (with the proviso that R is seededwith a different random number for each system). To authenticate ChipAand read ChipA's memory M:

-   -   System calls ChipT's Random function;    -   ChipT produces ad returns E_(KT)[R] to System;    -   System calls ChipA's Read function, passing in E_(KT)[R];    -   ChipA returns M|E_(KA)[R|M], first obtaining R by        D_(KA)[E_(KT)[R]];    -   System calls ChipT's Test function, passing in M and        E_(KA)[R|M];    -   ChipT calculates D_(KT)[E_(KA)[R|M]] and compares it to R|M.    -   System checks response from ChipT. If the response is 1, then        ChipA is considered authentic. If 0, ChipA is considered        invalid.

To authenticate a write of M_(new) to ChipA's memory M:

-   -   System calls ChipA's Write function, passing in M_(new);    -   The authentication procedure for a Read is carried out;    -   If ChipA is authentic and M_(new)=M, the write succeeded.        Otherwise it failed.

The data flow for read authentication is shown in FIG. 172. Only a validChipA would know the value of R, since R is not passed into theAuthenticate function (it is passed in as an encrypted value). R must beobtained by decrypting E[R], which can only be done using the secret keyK_(A). Once obtained, R must be appended to M and then the resultre-encoded. ChipT can then verify that the decoded form ofE_(KA)[R|M]=R|M and hence ChipA is valid. Since K_(T)≠K_(A),E_(KT)[R]≠E_(KA)[R]. Protocol 4 has the following advantages:

-   -   K_(A) (the secret key) is not revealed during the authentication        process    -   Given E_(KT)[X], a clone chip cannot generate X without K_(A) or        access to a real ChipA.    -   Since K_(T)≠K_(A), ChipT can be implemented completely in        software or in insecure hardware or as part of System. Only        ChipA is required to be a secure Authentication Chip.    -   Since ChipT and ChipA contain different keys, intense testing of        ChipT will reveal nothing about K_(A).    -   If ChipT is a physical chip, System is easy to design.    -   There are a number of well-documented and cryptanalyzed        asymmetric algorithms to chose from for implementation,        including patent-free and license-free solutions.    -   Even if System could be rewired so that ChipA requests were        directed to ChipT, ChipT could never answer for ChipA since        K_(T)≠K_(A). The attack would have to be directed at the System        ROM itself to bypass the Authentication protocol.

However, Protocol 4 has a number of disadvantages:

-   -   All Authentication Chips need to contain both asymmetric encrypt        and decrypt functionality. Consequently each chip is larger,        more complex, and more expensive than the chip required for        Protocol 3.    -   For satisfactory security, each key needs to be 2048 bits        (compared to a minimum of 128 bits for symmetric cryptography in        Protocol 1). The associated intermediate memory used by the        encryption and decryption algorithms is correspondingly larger.    -   Key generation is non-trivial. Random numbers are not good keys.    -   If ChipT is implemented as a core, there may be difficulties in        linking it into a given System ASIC.    -   If ChipT is implemented as software, not only is the        implementation of System open to programming error and        non-rigorous testing, but the integrity of the compiler and        mathematics primitives must be rigorously checked for each        implementation of System. This is more complicated and costly        than simply using a well-tested chip.    -   Although many symmetric algorithms are specifically strengthened        to be resistant to differential cryptanalysis (which is based on        chosen text attacks), the private key K_(A) is susceptible to a        chosen text attack

Protocol 4 Authentication Chips could not be exported from the USA,since they would be considered strong encryption devices.

As with Protocol 3, the only specific timing requirement of Protocol 4is that the return value of 0 (indicating a bad input) must be producedin the same amount of time regardless of where the error is in theinput. Attackers can therefore not learn anything about what was badabout the input value. This is true for both RD and TST functions.

Variation on Call to TST

If there are two Authentication Chips used, it is theoretically possiblefor a clone manufacturer to replace the System Authentication Chip withone that returns 1 (success) for each call to TST. The System can testfor this by calling TST a number of times−N times with a wrong hashvalue, and expect the result to be 0. The final time that TST is called,the true returned value from ChipA is passed, and the return value istrusted. The question then arises of how many times to call TST. Thenumber of calls must be random, so that a clone chip manufacturer cannotknow the number ahead of time. If System has a clock, bits from theclock can be used to determine how many false calls to TST should bemade. Otherwise the returned value from ChipA can be used. In the lattercase, an attacker could still rewire the System to permit a clone ChipTto view the returned value from ChipA, and thus know which hash value isthe correct one. The worst case of course, is that the System can becompletely replaced by a clone System that does not requireauthenticated consumables—this is the limit case of rewiring andchanging the System. For this reason, the variation on calls to TST isoptional, depending on the System, the Consumable, and how likelymodifications are to be made. Adding such logic to System (for examplein the case of a small desktop printer) may be considered notworthwhile, as the System is made more complicated. By contrast, addingsuch logic to a camera may be considered worthwhile.

Clone Consumable Using Real Authentication Chip

It is important to decrement the amount of consumable remaining beforeuse that consumable portion. If the consumable is used first, a cloneconsumable could fake a loss of contact during a write to the specialknown address and then appear as a fresh new consumable. It is importantto note that this attack still requires a real Authentication Chip ineach consumable.

Longevity of Key

A general problem of these two protocols is that once the authenticationkeys are chosen, it cannot easily be changed. In some instances akey-compromise is not a problem, while for others a key compromise isdisastrous.

Choosing a Protocol

Even if the choice of keys for Protocols 2 and 4 was straightforward,both protocols are impractical at the present time due to the high costof silicon implementation (both due to key size and functionalimplementation). Therefore Protocols 1 and 3 are the two protocols ofchoice. However, Protocols 1 and 3 contain much of the same components:

-   -   both require read and write access;    -   both require implementation of a keyed one-way function; and    -   both require random number generation functionality.

Protocol 3 requires an additional key (K₂), as well as some minimalstate machine changes:

-   -   a state machine alteration to enable F_(K1)[X] to be called        during Random;    -   a Test function which calls F_(K2)[X]    -   a state machine alteration to the Read function to call        F_(K1)[X] and F_(K2)[X]

Protocol 3 only requires minimal changes over Protocol 1. It is moresecure and can be used in all places where Presence Only Authenticationis required (Protocol 1). It is therefore the protocol of choice. Giventhat Protocols 1 and 3 both make use of keyed one-way functions, thechoice of one-way function is examined in more detail here. Thefollowing table outlines the attributes of the applicable choices. Theattributes are worded so that the attribute is seen as an advantage.

Triple Random HMAC- HMAC- HMAC- DES Blowfish RC5 IDEA Sequences MD5 SHA1RIPEMD160 Free of patents • • • • • • Random key generation • • • Can beexported from the USA • • • • Fast • • • • Preferred Key Size (bits) for168 128 128 128 512 128 160 160 use in this application Block size(bits)  64  64  64  64 256 512 512 512 Cryptanalysis Attack-Free • • • •• (apart from weak keys) Output size given input size N ≧N ≧N ≧N ≧N 128128 160 160 Low storage requirements • • • • Low silicon complexity • •• • NSA designed • •

An examination of the table shows that the choice is effectively betweenthe 3 HMAC constructs and the Random Sequence. The problem of key sizeand key generation eliminates the Random Sequence. Given that a numberof attacks have already been carried out on MD5 and since the hashresult is only 128 bits, HMAC-MD5 is also eliminated. The choice istherefore between HMAC-SHA1 and HMAC-RIPEMD160. RIPEMD-160 is relativelynew, and has not been as extensively cryptanalyzed as SHA1. However,SHA-1 was designed by the NSA, so this may be seen by some as a negativeattribute.

Given that there is not much between the two, SHA-1 will be used for theHMAC construct.

Choosing a Random Number Generator

Each of the protocols described (1-4) requires a random numbergenerator. The generator must be “good” in the sense that the randomnumbers generated over the life of all Systems cannot be predicted. Ifthe random numbers were the same for each System, an attacker couldeasily record the correct responses from a real Authentication Chip, andplace the responses into a ROM lookup for a clone chip. With such anattack there is no need to obtain K₁ or K₂. Therefore the random numbersfrom each System must be different enough to be unpredictable, ornon-deterministic. As such, the initial value for R (the random seed)should be programmed with a physically generated random number gatheredfrom a physically random phenomenon, one where there is no informationabout whether a particular bit will be 1 or 0. The seed for R must NOTbe generated with a computer-run random number generator. Otherwise thegenerator algorithm and seed may be compromised enabling an attacker togenerate and therefore know the set of all R values in all Systems.

Having a different R seed in each Authentication Chip means that thefirst R will be both random and unpredictable across all chips. Thequestion therefore arises of how to generate subsequent R values in eachchip.

The base case is not to change R at all. Consequently R and F_(K1)[R]will be the same for each call to Random[ ]. If they are the same, thenF_(K1)[R] can be a constant rather than calculated. An attacker couldthen use a single valid Authentication Chip to generate a valid lookuptable, and then use that lookup table in a clone chip programmedespecially for that System. A constant R is not secure.

The simplest conceptual method of changing R is to increment it by 1.Since R is random to begin with, the values across differing systems arestill likely to be random. However given an initial R, all subsequent Rvalues can be determined directly (there is no need to iterate 10,000times—R will take on values from R₀ to R₀+10000). An incrementing R isimmune to the earlier attack on a constant R. Since R is alwaysdifferent, there is no way to construct a lookup table for theparticular System without wasting as many real Authentication Chips asthe clone chip will replace.

Rather than increment using an adder, another way of changing R is toimplement it as an LFSR (Linear Feedback Shift Register). This has theadvantage of less silicon than an adder, but the advantage of anattacker not being able to directly determine the range of R for aparticular System, since an LFSR value-domain is determined bysequential access. To determine which values an given initial R willgenerate, an attacker must iterate through the possibilities andenumerate them. The advantages of a changing R are also evident in theLFSR solution. Since R is always different, there is no way to constructa lookup table for the particular System without using-up as many realAuthentication Chips as the clone chip will replace (and only for thatSystem). There is therefore no advantage in having a more complexfunction to change R. Regardless of the function, it will always bepossible for an attacker to iterate through the lifetime set of valuesin a simulation. The primary security lies in the initial randomness ofR. Using an LFSR to change R (apart from using less silicon than anadder) simply has the advantage of not being restricted to a consecutivenumeric range (i.e. knowing R, R_(N) cannot be directly calculated; anattacker must iterate through the LFSR N times).

The Random number generator within the Authentication Chip is thereforean LFSR with 160 bits. Tap selection of the 160 bits for amaximal-period LFSR (i.e. the LFSR will cycle through all 2¹⁶⁰−1 states,0 is not a valid state) yields bits 159, 4, 2, and 1, as shown in FIG.173. The LFSR is sparse, in that not many bits are used for feedback(only 4 out of 160 bits are used). This is a problem for cryptographicapplications, but not for this application of non-sequential numbergeneration. The 160-bit seed value for R can be any random number except0, since an LFSR filled with 0s will produce a never-ending stream of0s. Since the LFSR described is a maximal period LFSR, all 160 bits canbe used directly as R. There is no need to construct a numbersequentially from output bits of b₀. After each successful call to TST,the random number (R) must be advanced by XORing bits 1, 2, 4, and 159,and shifting the result into the high order bit. The new R andcorresponding F_(K1)[R] can be retrieved on the next call to Random.

Holding Out Against Logical Attacks

Protocol 3 is the authentication scheme used by the Authentication Chip.As such, it should be resistant to defeat by logical means. While theeffect of various types of attacks on Protocol 3 have been mentioned indiscussion, this section details each type of attack in turn withreference to Protocol 3.

Brute Force Attack

A Brute Force attack is guaranteed to break Protocol 3. However thelength of the key means that the time for an attacker to perform a bruteforce attack is too long to be worth the effort. An attacker only needsto break K₂ to build a clone Authentication Chip. K₁ is merely presentto strengthen K₂ against other forms of attack. A Brute Force Attack onK₂ must therefore break a 160-bit key. An attack against K₂ requires amaximum of 2¹⁶⁰ attempts, with a 50% chance of finding the key afteronly 2¹⁵⁹ attempts. Assuming an array of a trillion processors, eachrunning one million tests per second, 2¹⁵⁹ (7.3×10⁴⁷) tests takes2.3×10²³ years, which is longer than the lifetime of the universe. Thereare only 100 million personal computers in the world. Even if these wereall connected in an attack (e.g. via the Internet), this number is still10,000 times smaller than the trillion-processor attack described.Further, if the manufacture of one trillion processors becomes apossibility in the age of nanocomputers, the time taken to obtain thekey is longer than the lifetime of the universe.

Guessing the Key Attack

It is theoretically possible that an attacker can simply “guess thekey”. In fact, given enough time, and trying every possible number, anattacker will obtain the key. This is identical to the Brute Forceattack described above, where 2¹⁵⁹ attempts must be made before a 50%chance of success is obtained. The chances of someone simply guessingthe key on the first try is 2¹⁶⁰. For comparison, the chance of someonewinning the top prize in a U.S. state lottery and being killed bylightning in the same day is only 1 in 2⁶¹. The chance of someoneguessing the Authentication Chip key on the first go is 1 in 2¹⁶⁰, whichis comparative to two people choosing exactly the same atoms from achoice of all the atoms in the Earth i.e. extremely unlikely.

Quantum Computer Attack

To break K₂, a quantum computer containing 160 qubits embedded in anappropriate algorithm must be built. An attack against a 160-bit key isnot feasible. An outside estimate of the possibility of quantumcomputers is that 50 qubits may be achievable within 50 years. Evenusing a 50 qubit quantum computer, 2¹¹⁰ tests are required to crack a160 bit key. Assuming an array of 1 billion 50 qubit quantum computers,each able to try 2⁵⁰ keys in 1 microsecond (beyond the current wildestestimates) finding the key would take an average of 18 billion years.

Cyphertext Only Attack

An attacker can launch a Cyphertext Only attack on K₁ by callingmonitoring calls to RND and RD, and on K₂ by monitoring calls to RD andTST. However, given that all these calls also reveal the plaintext aswell as the hashed form of the plaintext, the attack would betransformed into a stronger form of attack—a Known Plaintext attack.

Known Plaintext Attack

It is easy to connect a logic analyzer to the connection between theSystem and the Authentication Chip, and thereby monitor the flow ofdata. This flow of data results in known plaintext and the hashed formof the plaintext, which can therefore be used to launch a KnownPlaintext attack against both K₁ and K₂. To launch an attack against K₁,multiple calls to RND and TST must be made (with the call to TST beingsuccessful, and therefore requiring a call to RD on a valid chip). Thisis straightforward, requiring the attacker to have both a SystemAuthentication Chip and a Consumable Authentication Chip. For each K₁ X,H_(K1)[X] pair revealed, a K₂ Y, H_(K2)[Y] pair is also revealed. Theattacker must collect these pairs for further analysis. The questionarises of how many pairs must be collected for a meaningful attack to belaunched with this data. An example of an attack that requirescollection of data for statistical analysis is DifferentialCryptanalysis. However, there are no known attacks against SHA-1 orHMAC-SHA1, so there is no use for the collected data at this time.

Chosen Plaintext Attacks

Given that the cryptanalyst has the ability to modify subsequent chosenplaintexts based upon the results of previous experiments, K₂ is open toa partial form of the Adaptive Chosen Plaintext attack, which iscertainly a stronger form of attack than a simple Chosen Plaintextattack. A chosen plaintext attack is not possible against K₁, sincethere is no way for a caller to modify R, which used as input to the RNDfunction (the only function to provide the result of hashing with K₁).Clearing R also has the effect of clearing the keys, so is not useful,and the SSI command calls CLR before storing the new R-value.

Adaptive Chosen Plaintext Attacks

This kind of attack is not possible against K₁, since K₁ is notsusceptible to chosen plaintext attacks. However, a partial form of thisattack is possible against K₂, especially since both System andconsumables are typically available to the attacker (the System may notbe available to the attacker in some instances, such as a specific car).The HMAC construct provides security against all forms of chosenplaintext attacks. This is primarily because the HMAC construct has 2secret input variables (the result of the original hash, and the secretkey). Thus finding collisions in the hash function itself when the inputvariable is secret is even harder than finding collisions in the plainhash function. This is because the former requires direct access toSHA-1 (not permitted in Protocol 3) in order to generate pairs ofinput/output from SHA-1. The only values that can be collected by anattacker are HMAC[R] and HMAC[R|M]. These are not attacks against theSHA-1 hash function itself, and reduce the attack to a DifferentialCryptanalysis attack, examining statistical differences betweencollected data. Given that there is no Differential Cryptanalysis attackknown against SHA-1 or HMAC, Protocol 3 is resistant to the AdaptiveChosen Plaintext attacks.

Purposeful Error Attack

An attacker can only launch a Purposeful Error Attack on the TST and RDfunctions, since these are the only functions that validate inputagainst the keys. With both the TST and RD functions, a 0 value isproduced if an error is found in the input—no further information isgiven. In addition, the time taken to produce the 0 result isindependent of the input, giving the attacker no information about whichbit(s) were wrong. A Purposeful Error Attack is therefore fruitless.

Chaining Attack

Any form of chaining attack assumes that the message to be hashed isover several blocks, or the input variables can somehow be set. TheHMAC-SHA1 algorithm used by Protocol 3 only ever hashes a single 512-bitblock at a time. Consequently chaining attacks are not possible againstProtocol 3.

Birthday Attack

The strongest attack known against HMAC is the birthday attack, based onthe frequency of collisions for the hash function. However this istotally impractical for minimally reasonable hash functions such asSHA-1. And the birthday attack is only possible when the attacker hascontrol over the message that is signed. Protocol 3 uses hashing as aform of digital signature. The System sends a number that must beincorporated into the response from a valid Authentication Chip. Sincethe Authentication Chip must respond with H[R|M], but has no controlover the input value R, the birthday attack is not possible. This isbecause the message has effectively already been generated and signed.An attacker must instead search for a collision message that hashes tothe same value (analogous to finding one person who shares yourbirthday). The clone chip must therefore attempt to find a new value R₂such that the hash of R₂ and a chosen M₂ yields the same hash value asH[R|M]. However the System Authentication Chip does not reveal thecorrect hash value (the TST function only returns 1 or 0 depending onwhether the hash value is correct). Therefore the only way of findingout the correct hash value (in order to find a collision) is tointerrogate a real Authentication Chip. But to find the correct valuemeans to update M, and since the decrement-only parts of M are one-way,and the read-only parts of M cannot be changed, a clone consumable wouldhave to update a real consumable before attempting to find a collision.The alternative is a Brute Force attack search on the TST function tofind a success (requiring each clone consumable to have access to aSystem consumable). A Brute Force Search, as described above, takeslonger than the lifetime of the universe, in this case, perauthentication. Due to the fact that a timely gathering of a hash valueimplies a real consumable must be decremented, there is no point for aclone consumable to launch this kind of attack.

Substitution with a Complete Lookup Table

The random number seed in each System is 160 bits. The worst casesituation for an Authentication Chip is that no state data is changed.Consequently there is a constant value returned as M. However a clonechip must still return F₁[R|M], which is a 160 bit value. Assuming a160-bit lookup of a 160-bit result, this requires 7.3×10⁴⁸ bytes, or6.6×10³⁶ terabytes, certainly more space than is feasible for the nearfuture. This of course does not even take into account the method ofcollecting the values for the ROM. A complete lookup table is thereforecompletely impossible.

Substitution with a Sparse Lookup Table

A sparse lookup table is only feasible if the messages sent to theAuthentication Chip are somehow predictable, rather than effectivelyrandom. The random number R is seeded with an unknown random number,gathered from a naturally random event. There is no possibility for aclone manufacturer to know what the possible range of R is for allSystems, since each bit has a 50% chance of being a 1 or a 0. Since therange of R in all systems is unknown, it is not possible to build asparse lookup table that can be used in all systems. The general sparselookup table is therefore not a possible attack. However, it is possiblefor a clone manufacturer to know what the range of R is for a givenSystem. This can be accomplished by loading a LFSR with the currentresult from a call to a specific System Authentication Chip's RNDfunction, and iterating some number of times into the future. If this isdone, a special ROM can be built which will only contain the responsesfor that particular range of R, i.e. a ROM specifically for theconsumables of that particular System. But the attacker still needs toplace correct information in the ROM. The attacker will therefore needto find a valid Authentication Chip and call it for each of the valuesin R.

Suppose the clone Authentication Chip reports a full consumable, andthen allows a single use before simulating loss of connection andinsertion of a new full consumable. The clone consumable would thereforeneed to contain responses for authentication of a full consumable andauthentication of a partially used consumable. The worst case ROMcontains entries for full and partially used consumables for R over thelifetime of System. However, a valid Authentication Chip must be used togenerate the information, and be partially used in the process. If agiven System only produces about n R-values, the sparse lookup-ROMrequired is 10n bytes multiplied by the number of different values forM. The time taken to build the ROM depends on the amount of timeenforced between calls to RD.

After all this, the clone manufacturer must rely on the consumerreturning for a refill, since the cost of building the ROM in the firstplace consumes a single consumable. The clone manufacturer's business insuch a situation is consequently in the refills. The time and cost then,depends on the size of R and the number of different values for M thatmust be incorporated in the lookup. In addition, a custom cloneconsumable ROM must be built to match each and every System, and adifferent valid Authentication Chip must be used for each System (inorder to provide the full and partially used data). The use of anAuthentication Chip in a System must therefore be examined to determinewhether or not this kind of attack is worthwhile for a clonemanufacturer. As an example, of a camera system that has about 10,000prints in its lifetime. Assume it has a single Decrement Only value(number of prints remaining), and a delay of 1 second between calls toRD. In such a system, the sparse table will take about 3 hours to build,and consumes 100K. Remember that the construction of the ROM requiresthe consumption of a valid Authentication Chip, so any money chargedmust be worth more than a single consumable and the clone consumablecombined. Thus it is not cost effective to perform this function for asingle consumable (unless the clone consumable somehow contained theequivalent of multiple authentic consumables). If a clone manufactureris going to go to the trouble of building a custom ROM for each owner ofa System, an easier approach would be to update System to completelyignore the Authentication Chip.

Consequently, this attack is possible as a per-System attack, and adecision must be made about the chance of this occurring for a givenSystem/Consumable combination. The chance will depend on the cost of theconsumable and Authentication Chips, the longevity of the consumable,the profit margin on the consumable, the time taken to generate the ROM,the size of the resultant ROM, and whether customers will come back tothe clone manufacturer for refills that use the same clone chip etc.

Differential Cryptanalysis

Existing differential attacks are heavily dependent on the structure ofS boxes, as used in DES and other similar algorithms. Although otheralgorithms such as HMAC-SHA1 used in Protocol 3 have no S boxes, anattacker can undertake a differential-like attack by undertakingstatistical analysis of:

-   -   Minimal-difference inputs, and their corresponding outputs    -   Minimal-difference outputs, and their corresponding inputs

To launch an attack of this nature, sets of input/output pairs must becollected. The collection from Protocol 3 can be via Known Plaintext, orfrom a Partially Adaptive Chosen Plaintext attack. Obviously the latter,being chosen, will be more useful. Hashing algorithms in general aredesigned to be resistant to differential analysis. SHA-1 in particularhas been specifically strengthened, especially by the 80 word expansionso that minimal differences in input produce will still produce outputsthat vary in a larger number of bit positions (compared to 128 bit hashfunctions). In addition, the information collected is not a direct SHA-1input/output set, due to the nature of the HMAC algorithm. The HMACalgorithm hashes a known value with an unknown value (the key), and theresult of this hash is then rehashed with a separate unknown value.Since the attacker does not know the secret value, nor the result of thefirst hash, the inputs and outputs from SHA-1 are not known, making anydifferential attack extremely difficult. The following is a moredetailed discussion of minimally different inputs and outputs from theAuthentication Chip.

Minimal Difference Inputs

This is where an attacker takes a set of X, F_(K)[X] values where the Xvalues are minimally different, and examines the statistical differencesbetween the outputs F_(K)[X]. The attack relies on X values that onlydiffer by a minimal number of bits. The question then arises as to howto obtain minimally different X values in order to compare the F_(K)[X]values. K₁: With K₁, the attacker needs to statistically examineminimally different X, F_(K1)[X] pairs. However the attacker cannotchoose any X value and obtain a related F_(K1)[X] value. Since X,F_(K1)[X] pairs can only be generated by calling the RND function on aSystem Authentication Chip, the attacker must call RND multiple times,recording each observed pair in a table. A search must then be madethrough the observed values for enough minimally different X values toundertake a statistical analysis of the F_(K1)[X] values.

K₂: With K₂, the attacker needs to statistically examine minimallydifferent X, F_(K2)[X] pairs. The only way of generating X, F_(K2)[X]pairs is via the RD function, which produces F_(K2)[X] for a given Y,F_(K1)[Y] pair, where X=Y|M. This means that Y and the changeable partof M can be chosen to a limited extent by an attacker. The amount ofchoice must therefore be limited as much as possible. The first way oflimiting an attacker's choice is to limit Y, since RD requires an inputof the format Y, F_(K1)[Y]. Although a valid pair can be readilyobtained from the RND function, it is a pair of RND's choosing. Anattacker can only provide their own Y if they have obtained theappropriate pair from RND, or if they know K₁. Obtaining the appropriatepair from RND requires a Brute Force search. Knowing K₁ is onlylogically possible by performing cryptanalysis on pairs obtained fromthe RND function—effectively a known text attack. Although RND can onlybe called so many times per second, K₁ is common across System chips.Therefore known pairs can be generated in parallel.

The second way to limit an attacker's choice is to limit M, or at leastthe attacker's ability to choose M. The limiting of M is done by makingsome parts of M Read Only, yet different for each Authentication Chip,and other parts of M Decrement Only. The Read Only parts of M shouldideally be different for each Authentication Chip, so could beinformation such as serial numbers, batch numbers, or random numbers.The Decrement Only parts of M mean that for an attacker to try adifferent M, they can only decrement those parts of M so manytimes—after the Decrement Only parts of M have been reduced to 0 thoseparts cannot be changed again. Obtaining a new Authentication chip 53provides a new M, but the Read Only portions will be different from theprevious Authentication Chip's Read Only portions, thus reducing anattacker's ability to choose M even further. Consequently an attackercan only gain a limited number of chances at choosing values for Y andM.

Minimal Difference Outputs

This is where an attacker takes a set of X, F_(K)[X] values where theF_(K)[X] values are minimally different, and examines the statisticaldifferences between the X values. The attack relies on F_(K)[X] valuesthat only differ by a minimal number of bits. For both K₁ and K₂, thereis no way for an attacker to generate an X value for a given F_(K)[X].To do so would violate the fact that F is a one-way function.Consequently the only way for an attacker to mount an attack of thisnature is to record all observed X, F_(K)[X] pairs in a table. A searchmust then be made through the observed values for enough minimallydifferent F_(K)[X] values to undertake a statistical analysis of the Xvalues. Given that this requires more work than a minimally differentinput attack (which is extremely limited due to the restriction on M andthe choice of R), this attack is not fruitful.

Message Substitution Attacks

In order for this kind of attack to be carried out, a clone consumablemust contain a real Authentication chip 53, but one that is effectivelyreusable since it never gets decremented. The clone Authentication Chipwould intercept messages, and substitute its own. However this attackdoes not give success to the attacker. A clone Authentication Chip maychoose not to pass on a WR command to the real Authentication Chip.However the subsequent RD command must return the correct response (asif the WR had succeeded). To return the correct response, the hash valuemust be known for the specific R and M. As described in the BirthdayAttack section, an attacker can only determine the hash value byactually updating M in a real Chip, which the attacker does not want todo. Even changing the R sent by System does not help since the SystemAuthentication Chip must match the R during a subsequent TST. A Messagesubstitution attack would therefore be unsuccessful. This is only trueif System updates the amount of consumable remaining before it is used.

Reverse Engineering the Key Generator

If a pseudo-random number generator is used to generate keys, there isthe potential for a clone manufacture to obtain the generator program orto deduce the random seed used. This was the way in which the Netscapesecurity program was initially broken.

Bypassing Authentication Altogether

Protocol 3 requires the System to update the consumable state databefore the consumable is used, and follow every write by a read (toauthenticate the write). Thus each use of the consumable requires anauthentication. If the System adheres to these two simple rules, a clonemanufacturer will have to simulate authentication via a method above(such as sparse ROM lookup).

Reuse of Authentication Chips

As described above, Protocol 3 requires the System to update theconsumable state data before the consumable is used, and follow everywrite by a read (to authenticate the write). Thus each use of theconsumable requires an authentication. If a consumable has been used up,then its Authentication Chip will have had the appropriate state-datavalues decremented to 0. The chip can therefore not be used in anotherconsumable. Note that this only holds true for Authentication Chips thathold Decrement-Only data items. If there is no state data decrementedwith each usage, there is nothing stopping the reuse of the chip. Thisis the basic difference between Presence-Only Authentication andConsumable Lifetime Authentication. Protocol 3 allows both. The bottomline is that if a consumable has Decrement Only data items that are usedby the System, the Authentication Chip cannot be reused without beingcompletely reprogrammed by a valid Programming Station that hasknowledge of the secret key.

Management Decision to Omit Authentication to Save Costs

Although not strictly an external attack, a decision to omitauthentication in future Systems in order to save costs will have widelyvarying effects on different markets. In the case of high volumeconsumables, it is essential to remember that it is very difficult tointroduce authentication after the market has started, as systemsrequiring authenticated consumables will not work with older consumablesstill in circulation. Likewise, it is impractical to discontinueauthentication at any stage, as older Systems will not work with thenew, unauthenticated, consumables. In the second case, older Systems canbe individually altered by replacing the System Authentication Chip by asimple chip that has the same programming interface, but whose TSTfunction always succeeds. Of course the System may be programmed to testfor an always-succeeding TST function, and shut down. In the case of aspecialized pairing, such as a car/car-keys, or door/door-key, or someother similar situation, the omission of authentication in futuresystems is trivial and non-repercussive. This is because the consumer issold the entire set of System and Consumable Authentication Chips at theone time.

Garrote/Bribe Attack

This form of attack is only successful in one of two circumstances:

-   -   K₁, K₂, and R are already recorded by the chip-programmer, or    -   the attacker can coerce future values of K₁, K₂, and R to be        recorded.

If humans or computer systems external to the Programming Station do notknow the keys, there is no amount of force or bribery that can revealthem. The level of security against this kind of attack is ultimately adecision for the System/Consumable owner, to be made according to thedesired level of service. For example, a car company may wish to keep arecord of all keys manufactured, so that a person can request a new keyto be made for their car. However this allows the potential compromiseof the entire key database, allowing an attacker to make keys for any ofthe manufacturer's existing cars. It does not allow an attacker to makekeys for any new cars. Of course, the key database itself may also beencrypted with a further key that requires a certain number of people tocombine their key portions together for access. If no record is kept ofwhich key is used in a particular car, there is no way to makeadditional keys should one become lost. Thus an owner will have toreplace his car's Authentication Chip and all his car-keys. This is notnecessarily a bad situation. By contrast, in a consumable such as aprinter ink cartridge, the one key combination is used for all Systemsand all consumables. Certainly if no backup of the keys is kept, thereis no human with knowledge of the key, and therefore no attack ispossible. However, a no-backup situation is not desirable for aconsumable such as ink cartridges, since if the key is lost no moreconsumables can be made. The manufacturer should therefore keep a backupof the key information in several parts, where a certain number ofpeople must together combine their portions to reveal the full keyinformation. This may be required if case the chip programming stationneeds to be reloaded. In any case, none of these attacks are againstProtocol 3 itself, since no humans are involved in the authenticationprocess. Instead, it is an attack against the programming stage of thechips.

HMAC-SHA1

The mechanism for authentication is the HMAC-SHA1 algorithm, acting onone of:

-   -   HMAC-SHA1 (R, K₁), or    -   HMAC-SHA1 (R|M, K₂)

We will now examine the HMAC-SHA1 algorithm in greater detail thancovered so far, and describes an optimization of the algorithm thatrequires fewer memory resources than the original definition.

HMAC

The HMAC algorithm proceeds, given the following definitions:

-   -   H=the hash function (e.g. MD5 or SHA-1)    -   n=number of bits output from H (e.g. 160 for SHA-1, 128 bits for        MD5)    -   M=the data to which the MAC function is to be applied    -   K=the secret key shared by the two parties    -   ipad=0x36 repeated 64 times    -   opad=0x5C repeated 64 times

The HMAC algorithm is as follows:

-   -   Extend K to 64 bytes by appending 0x00 bytes to the end of K    -   XOR the 64 byte string created in (1) with ipad    -   Append data stream M to the 64 byte string created in (2)    -   Apply H to the stream generated in (3)    -   XOR the 64 byte string created in (1) with opad    -   Append the H result from (4) to the 64 byte string resulting        from (5)    -   Apply H to the output of (6) and output the result

Thus:

-   -   HMAC[M]=H[(K⊕opad)|H[(K⊕ipad)|M]]

HMAC-SHA1 algorithm is simply HMAC with H=SHA-1.

SHA-1

The SHA1 hashing algorithm is defined in the algorithm as summarizedhere.

Nine 32-bit constants are defined. There are 5 constants used toinitialize the chaining variables, and there are 4 additive constants.

Initial Chaining Additive Values Constants h₁ 0x67452301 y₁ 0x5A827999h₂ 0xEFCDAB89 y₂ 0x6ED9EBA1 h₃ 0x98BADCFE y₃ 0x8F1BBCDC h₄ 0x10325476 y₄0xCA62C1D6 h₅ 0xC3D2E1F0

Non-optimized SHA-1 requires a total of 2912 bits of data storage:

-   -   Five 32-bit chaining variables are defined: H₁, H₂, H₃, H₄ and        H₅.    -   Five 32-bit working variables are defined: A, B, C, D, and E.    -   One 32-bit temporary variable is defined: t.    -   Eighty 32-bit temporary registers are defined: X₀₋₇₉.

The following functions are defined for SHA-1:

Symbolic Nomenclature Description + Addition modulo 2³² X

Y Result of rotating X left through Y bit positions f(X, Y, Z) (X

 Y)

 (~X

 Z) g(X, Y, Z) (X

 Y)

 (X

 Z)

 (Y

 Z) h(X, Y, Z) X ⊕ Y ⊕ Z

The hashing algorithm consists of firstly padding the input message tobe a multiple of 512 bits and initializing the chaining variables H₁₋₅with h₁₋₅. The padded message is then processed in 512-bit chunks, withthe output hash value being the final 160-bit value given by theconcatenation of the chaining variables: H₁|H₂|H₃|H₄|H₅. The steps ofthe SHA-1 algorithm are now examined in greater detail.

Step 1. Preprocessing

The first step of SHA-1 is to pad the input message to be a multiple of512 bits as follows and to initialize the chaining variables.

Steps to follow to preprocess the input message Pad the input messageAppend a 1 bit to the message Append 0 bits such that the length of thepadded message is 64-bits short of a multiple of 512 bits. Append a64-bit value containing the length in bits of the original inputmessage. Store the length as most significant bit through to leastsignificant bit. Initialize the H₁ ← h₁, H₂ ← h₂, H₃ ← h₃, H₄ ← h₄, H₅ ←h₅ chaining variables

Step 2. Processing

The padded input message can now be processed. We process the message in512-bit blocks. Each 512-bit block is in the form of 16×32-bit words,referred to as InputWord₀₋₁₅.

Steps to follow for each 512 bit block (InputWord₀₋₁₅) Copy the 512 Forj = 0 to 15 input bits X_(j) = InputWord_(j) into X₀₋₁₅ Expand X₀₋₁₅ Forj = 16 to 79 into X₁₆₋₇₉ Xj ← ((X_(j−3) ⊕ X_(j−8) ⊕ X_(j−14) ⊕ X_(j−16))

 1) Initialize working A ← H₁, B ← H₂, C ← H₃, D ← H₄, E ← H₅ variablesRound 1 For j = 0 to 19 t ← ((A

 5) + f(B, C, D) + E + Xj + y₁) E ← D, D ← C, C ← (B

30), B ← A, A ← t Round 2 For j = 20 to 39 t ← ((A

5) + h(B, C, D) + E + X_(j) + y₂) E ← D, D ← C, C ← (B

30), B ← A, A ← t Round 3 For j = 40 to 59 t t ← ((A

5) + g(B, C, D) + E + X_(j) + y₃) E ← D, D ← C, C ← (B

30), B ← A, A ← t Round 4 For j = 60 to 79 t ← ((A

5) + h(B, C, D) + E + X_(j) + y₄) E ← D, D ← C, C ← (B

30), B ← A, A ← t Update chaining H₁ ← _(H1) + A, H₂ ← H₂ + B, variablesH₃ ← H₃ + C, H₄ ← H₄ + D, H₅ ← H₅ + E

Step 3. Completion

After all the 512-bit blocks of the padded input message have beenprocessed, the output hash value is the final 160-bit value given by:H₁|H₂|H₃|H₄|H₅.

Optimization for Hardware Implementation

The SHA-1 Step 2 procedure is not optimized for hardware. In particular,the 80 temporary 32-bit registers use up valuable silicon on a hardwareimplementation. This section describes an optimization to the SHA-1algorithm that only uses 16 temporary registers. The reduction insilicon is from 2560 bits down to 512 bits, a saving of over 2000 bits.It may not be important in some applications, but in the AuthenticationChip storage space must be reduced where possible. The optimization isbased on the fact that although the original 16-word message block isexpanded into an 80-word message block, the 80 words are not updatedduring the algorithm. In addition, the words rely on the previous 16words only, and hence the expanded words can be calculated on-the-flyduring processing, as long as we keep 16 words for the backwardreferences. We require rotating counters to keep track of which registerwe are up to using, but the effect is to save a large amount of storage.Rather than index X by a single value j, we use a 5 bit counter to countthrough the iterations. This can be achieved by initializing a 5-bitregister with either 16 or 20, and decrementing it until it reaches 0.In order to update the 16 temporary variables as if they were 80, werequire 4 indexes, each a 4-bit register. All 4 indexes increment (withwraparound) during the course of the algorithm.

Steps to follow for each 512 bit block (InputWord₀₋₁₅) Initializeworking A ← H₁, B ← H₂, C ← H₃, D ← H₄, E ← H₅ variables N₁ ← 13, N₂ ←8, N₃ ← 2, N₄ ← 0 Round 0 Do 16 times: Copy the 512 input bits X_(N4) =InputWord_(N4) into X₀₋₁₅ [

N₁,

N₂,

N₃]_(optional)

N₄ Round 1A Do 16 times: t ← ((A

5) + f(B, C, D) + E + X_(N4) + y₁) [

N₁,

N₂,

N₃]_(optional)

N₄ E ← D, D ← C, C ← (B

30), B ← A, A ← t Round 1B Do 4 times: X_(N4) ← ((X_(N1) ⊕ X_(N2) ⊕X_(N3) ⊕ X_(N4)) 1) t ← ((A

5) + f(B, C, D) + E + X_(N4) + y₁)

N₁,

N₂,

N₃,

N₄ E ← D, D ← C, C ← (B

30), B ← A, A ← t Round 2 Do 20 times: X_(N4) ← ((X_(N1) ⊕ X_(N2) ⊕X_(N3) ⊕ X_(N4))

 1) t ← ((A 5) + h(B, C, D) + E + X_(N4) + y₂)

N₁,

N₂,

N₃,

N₄ E ← D, D ← C, C ← (B

30), B ← A, A ← t Round 3 Do 20 times: X_(N4) ← ((X_(N1) ⊕ X_(N2) ⊕X_(N3) ⊕ X_(N4))

 1) t ← ((A

5) + g(B, C, D) + E + X_(N4) + y₃)

N₁,

N₂,

N₃,

N₄ E ← D, D ← C, C ← (B

30), B ← A, A ← t Round 4 Do 20 times: X_(N4) ← ((X_(N1) ⊕ X_(N2) ⊕X_(N3) ⊕ X_(N4))

 1) t ← ((A

5) + h(B, C, D) + E + X_(N4) + y₄)

N₁,

N₂,

N₃,

N₄ E ← D, D ← C, C ← (B

30), B ← A, A ← t Update chaining H₁ ← H₁ + A, H₂ ← H₂ + B, variables H₃← H₃ + C, H₄ ← H₄ + D, H₅ ← H₅ + E

The incrementing of N₁, N₂, and N₃ during Rounds 0 and 1A is optional. Asoftware implementation would not increment them, since it takes time,and at the end of the 16 times through the loop, all 4 counters will betheir original values. Designers of hardware may wish to increment all 4counters together to save on control logic. Round 0 can be completelyomitted if the caller loads the 512 bits of X₀₋₁₅.

HMAC-SHA1

In the Authentication Chip implementation, the HMAC-SHA1 unit only everperforms hashing on two types of inputs: on R using K₁ and on R|M usingK₂. Since the inputs are two constant lengths, rather than have HMAC andSHA-1 as separate entities on chip, they can be combined and thehardware optimized. The padding of messages in SHA-1 Step 1 (a 1 bit, astring of 0 bits, and the length of the message) is necessary to ensurethat different messages will not look the same after padding. Since weonly deal with 2 types of messages, our padding can be constant 0s. Inaddition, the optimized version of the SHA-1 algorithm is used, whereonly 16 32-bit words are used for temporary storage. These 16 registersare loaded directly by the optimized HMAC-SHA1 hardware.

The Nine 32-bit constants h₁₋₅ and y₁₋₄ are still required, although thefact that they are constants is an advantage for hardwareimplementation. Hardware optimized HMAC-SHA-1 requires a total of 1024bits of data storage:

-   -   Five 32-bit chaining variables are defined: H₁, H₂, H₃, H₄ and        H₅.    -   Five 32-bit working variables are defined: A, B, C, D, and E.    -   Five 32-bit variables for temporary storage and final result:        Buff160₁₋₅    -   One 32 bit temporary variable is defined: t.    -   Sixteen 32-bit temporary registers are defined: X₀₋₁₅.

The following two sections describe the steps for the two types of callsto HMAC-SHA1.

H[R, K₁]

In the case of producing the keyed hash of R using K₁, the originalinput message R is a constant length of 160 bits. We can therefore takeadvantage of this fact during processing. Rather than load X₀₋₁₅ duringthe first part of the SHA-1 algorithm, we load X₀₋₁₅ directly, andthereby omit Round 0 of the optimized Process Block (Step 2) of SHA-1.The pseudocode takes on the following steps:

Step Description Action 1 Process K ⊕ ipad X₀₋₄ ← K₁ ⊕ 0x363636 . . . 2X₅₋₁₅ ← 0x363636 . . . 3 H₁₋₅ ← h₁₋₅ 4 Process Block 5 Process R X₀₋₄ ←R 6 X₅₋₁₅ ← 0 7 Process Block 8 Buff160₁₋₅ ← H₁₋₅ 9 Process K ⊕ opadX₀₋₄ ← K₁ ⊕ 0x5C5C5C . . . 10 X₅₋₁₅ ← 0x5C5C5C . . . 11 H₁₋₅ ← h₁₋₅ 12Process Block 13 Process previous H[x] X₀₋₄ ← Result 14 X₅₋₁₅ ← 0 15Process Block 16 Get results Buff160₁₋₅ ← H₁₋₅

H[R|M, K₂]

In the case of producing the keyed hash of R|M using K₂, the originalinput message is a constant length of 416 (256+160) bits. We cantherefore take advantage of this fact during processing. Rather thanload X₀₋₁₅ during the first part of the SHA-1 algorithm, we load X₀₋₁₅directly, and thereby omit Round 0 of the optimized Process Block (Step2) of SHA-1. The pseudocode takes on the following steps:

Step Description Action 1 Process K ⊕ ipad X₀₋₄ ← K₂ ⊕ 0x363636 . . . 2X₅₋₁₅ ← 0x363636 . . . 3 H₁₋₅ ← h₁₋₅ 4 Process Block 5 Process R | MX₀₋₄ ← R 6 X₅₋₁₂ ← M 7 X₁₃₋₁₅ ←0 8 Process Block 9 Temp ← H₁₋₅ 10Process K ⊕ opad X₀₋₄← K₂ ⊕ 0x5C5C5C . . . 11 X₅₋₁₅ ← 0x5C5C5C . . . 12H₁₋₅ ← h₁₋₅ 13 Process Block 14 Process previous H[x] X₀₋₄ ←Temp 15X₅₋₁₅ ← 0 16 Process Block 17 Get results Result ← H₁₋₅

Data Storage Integrity

Each Authentication Chip contains some non-volatile memory in order tohold the variables required by Authentication Protocol 3. The followingnon-volatile variables are defined:

Size Variable Name (in bits) Description M[0 . . . 15] 256 16 words(each 16 bits) containing state data such as serial numbers, mediaremaining etc. K₁ 160 Key used to transform R during authentication. K₂160 Key used to transform M during authentication. R 160 Current randomnumber AccessMode[0 . . . 15] 32 The 16 sets of 2-bit AccessMode valuesfor M[n]. MinTicks 32 The minimum number of clock ticks between calls tokey-based functions SIWritten 1 If set, the secret key information (K₁,K₂, and R) has been written to the chip. If clear, the secretinformation has not been written yet. IsTrusted 1 If set, the RND andTST functions can be called, but RD and WR functions cannot be called.If clear, the RND and TST functions cannot be called, but RD and WRfunctions can be called. Total bits 802

Note that if these variables are in Flash memory, it is not a simplematter to write a new value to replace the old. The memory must beerased first, and then the appropriate bits set. This has an effect onthe algorithms used to change Flash memory based variables. For example,Flash memory cannot easily be used as shift registers. To update a Flashmemory variable by a general operation, it is necessary to follow thesesteps:

Read the entire N bit value into a general purpose register;Perform the operation on the general purpose register;Erase the Flash memory corresponding to the variable; andSet the bits of the Flash memory location based on the bits set in thegeneral-purpose register.

A RESET of the Authentication Chip has no effect on these non-volatilevariables.

M and AccessMode

Variables M[0] through M[15] are used to hold consumable state data,such as serial numbers, batch numbers, and amount of consumableremaining. Each M[n] register is 16 bits, making the entire M vector 256bits (32 bytes). Clients cannot read from or written to individual M[n]variables. Instead, the entire vector, referred to as M, is read orwritten in a single logical access. M can be read using the RD (read)command, and written to via the WR (write) command. The commands onlysucceed if K₁ and K₂ are both defined (SIWritten=1) and theAuthentication Chip is a consumable non-trusted chip (IsTrusted=0).Although M may contain a number of different data types, they differonly in their write permissions. Each data type can always be read. Oncein client memory, the 256 bits can be interpreted in any way chosen bythe client. The entire 256 bits of M are read at one time instead of insmaller amounts for reasons of security, as described in the chapterentitled Authentication. The different write permissions are outlined inthe following table:

Data Type Access Note Read Only Can never be written to ReadWrite Canalways be written to Decrement Can only be written to if the new valueis less than the old Only value. Decrement Only values are typically16-bit or 32-bit values, but can be any multiple of 16 bits.

To accomplish the protection required for writing, a 2-bit access modevalue is defined for each M[n]. The following table defines theinterpretation of the 2-bit access mode bit-pattern:

Bits Op Interpretation Action taken during Write command 00 RW ReadWriteThe new 16-bit value is always written to M[n]. 01 MSR Decrement OnlyThe new 16-bit value is only (Most written to M[n] if it is Significantless than the value currently in Region) M[n]. This is used for accessto the Most Significant 16 bits of a Decrement Only number. 10 NMSRDecrement Only The new 16-bit value is only (Not the Most written toM[n] if M[n + 1] Significant can also be written. The Region) NMSRaccess mode allows multiple precision values of 32 bits and more(multiples of 16 bits) to decrement. 11 RO Read Only The new 16-bitvalue is ignored. M[n] is left unchanged.

The 16 sets of access mode bits for the 16 M[n] registers are gatheredtogether in a single 32-bit AccessMode register. The 32 bits of theAccessMode register correspond to M[n] with n as follows:

MSB LSB 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 0

Each 2-bit value is stored in hi/lo format. Consequently, if M[0-5] wereaccess mode MSR, with M[6-15] access mode RO, the 32-bit AccessModeregister would be:

-   -   11-11-11-11-11-11-11-11-11-11-01-01-01-01-01-01

During execution of a WR (write) command, AccessMode[n] is examined foreach M[n], and a decision made as to whether the new M[n] value willreplace the old. The AccessMode register is set using the AuthenticationChip's SAM (Set Access Mode) command. Note that the Decrement Onlycomparison is unsigned, so any Decrement Only values that requirenegative ranges must be shifted into a positive range. For example, aconsumable with a Decrement Only data item range of −50 to 50 must havethe range shifted to be 0 to 100. The System must then interpret therange 0 to 100 as being −50 to 50. Note that most instances of DecrementOnly ranges are N to 0, so there is no range shift required. ForDecrement Only data items, arrange the data in order from mostsignificant to least significant 16-bit quantities from M[n] onward. Theaccess mode for the most significant 16 bits (stored in M[n]) should beset to MSR. The remaining registers (M[n+1], M[n+2] etc) should havetheir access modes set to NMSR. If erroneously set to NMSR, with noassociated MSR region, each NMSR region will be considered independentlyinstead of being a multi-precision comparison.

K₁

K₁ is the 160-bit secret key used to transform R during theauthentication protocol. K₁ is programmed along with K₂ and R with theSSI (Set Secret Information) command. Since K₁ must be kept secret,clients cannot directly read K₁. The commands that make use of K₁ areRND and RD. RND returns a pair R, F_(K1)[R] where R is a random number,while RD requires an X, F_(K1)[X] pair as input. K₁ is used in the keyedone-way hash function HMAC-SHA1. As such it should be programmed with aphysically generated random number, gathered from a physically randomphenomenon. K₁ must NOT be generated with a computer-run random numbergenerator. The security of the Authentication chips depends on K₁, K₂and R being generated in a way that is not deterministic. For example,to set K₁, a person can toss a fair coin 160 times, recording heads as1, and tails as 0. K₁ is automatically cleared to 0 upon execution of aCLR command. It can only be programmed to a non-zero value by the SSIcommand.

K₂

K₂ is the 160-bit secret key used to transform M|R during theauthentication protocol. K₂ is programmed along with K₁ and R with theSSI (Set Secret Information) command. Since K₂ must be kept secret,clients cannot directly read K₂. The commands that make use of K₂ are RDand TST. RD returns a pair M, F_(K2)[M|X] where X was passed in as oneof the parameters to the RD function. TST requires an M, F_(K2)[M|R]pair as input, where R was obtained from the Authentication Chip's RNDfunction. K₂ is used in the keyed one-way hash function HMAC-SHA1. Assuch it should be programmed with a physically generated random number,gathered from a physically random phenomenon. K₂ must NOT be generatedwith a computer-run random number generator. The security of theAuthentication chips depends on K₁, K₂ and R being generated in a waythat is not deterministic. For example, to set K₂, a person can toss afair coin 160 times, recording heads as 1, and tails as 0. K₂ isautomatically cleared to 0 upon execution of a CLR command. It can onlybe programmed to a non-zero value by the SSI command.

R and IsTrusted

R is a 160-bit random number seed that is programmed along with K₁ andK₂ with the SSI (Set Secret Information) command. R does not have to bekept secret, since it is given freely to callers via the RND command.However R must be changed only by the Authentication Chip, and not setto any chosen value by a caller. R is used during the TST command toensure that the R from the previous call to RND was used to generate theF_(K2)[M|R] value in the non-trusted Authentication Chip (ChipA). BothRND and TST are only used in trusted Authentication Chips (ChipT).IsTrusted is a 1-bit flag register that determines whether or not theAuthentication Chip is a trusted chip (ChipT):

-   -   If the IsTrusted bit is set, the chip is considered to be a        trusted chip, and hence clients can call RND and TST functions        (but not RD or WR).    -   If the IsTrusted bit is clear, the chip is not considered to be        trusted. Therefore RND and TST functions cannot be called (but        RD and WR functions can be called instead). System never needs        to call RND or TST on the consumable (since a clone chip would        simply return 1 to a function such as TST, and a constant value        for RND).

The IsTrusted bit has the added advantage of reducing the number ofavailable R, F_(K1)[R] pairs obtainable by an attacker, yet stillmaintain the integrity of the Authentication protocol. To obtain validR, F_(K1)[R] pairs, an attacker requires a System Authentication Chip,which is more expensive and less readily available than the consumables.Both R and the IsTrusted bit are cleared to 0 by the CLR command. Theyare both written to by the issuing of the SSI command. The IsTrusted bitcan only set by storing a non-zero seed value in R via the SSI command(R must be non-zero to be a valid LFSR state, so this is quitereasonable). R is changed via a 160-bit maximal period LFSR with taps onbits 1, 2, 4, and 159, and is changed only by a successful call to TST(where 1 is returned).

Authentication Chips destined to be trusted Chips used in Systems(ChipT) should have their IsTrusted bit set during programming, andAuthentication Chips used in Consumables (ChipA) should have theirIsTrusted bit kept clear (by storing 0 in R via the SSI command duringprogramming). There is no command to read or write the IsTrusted bitdirectly. The security of the Authentication Chip does not only relyupon the randomness of K₁ and K₂ and the strength of the HMAC-SHA1algorithm. To prevent an attacker from building a sparse lookup table,the security of the Authentication Chip also depends on the range of Rover the lifetime of all Systems. What this means is that an attackermust not be able to deduce what values of R there are in produced andfuture Systems. As such R should be programmed with a physicallygenerated random number, gathered from a physically random phenomenon. Rmust NOT be generated with a computer-run random number generator. Thegeneration of R must not be deterministic. For example, to generate an Rfor use in a trusted System chip, a person can toss a fair coin 160times, recording heads as 1, and tails as 0. 0 is the only non-validinitial value for a trusted R is 0 (or the IsTrusted bit will not beset).

SIWritten

The SIWritten (Secret Information Written) 1-bit register holds thestatus of the secret information stored within the Authentication Chip.The secret information is K₁, K₂ and R. A client cannot directly accessthe SIWritten bit. Instead, it is cleared via the CLR command (whichalso clears K₁, K₂ and R). When the Authentication Chip is programmedwith secret keys and random number seed using the SSI command(regardless of the value written), the SIWritten bit is setautomatically. Although R is strictly not secret, it must be writtentogether with K₁ and K₂ to ensure that an attacker cannot generate theirown random number seed in order to obtain chosen R, F_(K1)[R] pairs.

The SIWritten status bit is used by all functions that access K₁, K₂, orR. If the SIWritten bit is clear, then calls to RD, WR, RND, and TST areinterpreted as calls to CLR.

MinTicks

There are two mechanisms for preventing an attacker from generatingmultiple calls to TST and RD functions in a short period of time. Thefirst is a clock limiting hardware component that prevents the internalclock from operating at a speed more than a particular maximum (e.g. 10MHz). The second mechanism is the 32-bit MinTicks register, which isused to specify the minimum number of clock ticks that must elapsebetween calls to key-based functions. The MinTicks variable is clearedto 0 via the CLR command. Bits can then be set via the SMT (SetMinTicks) command. The input parameter to SMT contains the bit patternthat represents which bits of MinTicks are to be set. The practicaleffect is that an attacker can only increase the value in MinTicks(since the SMT function only sets bits). In addition, there is nofunction provided to allow a caller to read the current value of thisregister. The value of MinTicks depends on the operating clock speed andthe notion of what constitutes a reasonable time between key-basedfunction calls (application specific). The duration of a single tickdepends on the operating clock speed. This is the maximum of the inputclock speed and the Authentication Chip's clock-limiting hardware. Forexample, the Authentication Chip's clock-limiting hardware may be set at10 MHz (it is not changeable), but the input clock is 1 MHz. In thiscase, the value of 1 tick is based on 1 MHz, not 10 MHz. If the inputclock was 20 MHz instead of 1 MHz, the value of 1 tick is based on 10MHz (since the clock speed is limited to 10 MHz).

Once the duration of a tick is known, the MinTicks value can to be set.The value for MinTicks is the minimum number of ticks required to passbetween calls to the key-based RD and TST functions. The value is areal-time number, and divided by the length of an operating tick.Suppose the input clock speed matches the maximum clock speed of 10 MHz.If we want a minimum of 1 second between calls to key based functions,the value for MinTicks is set to 10,000,000. Consider an attackerattempting to collect X, F_(K1)[X] pairs by calling RND, RD and TSTmultiple times. If the MinTicks value is set such that the amount oftime between calls to TST is 1 second, then each pair requires 1 secondto generate. To generate 2²⁵ pairs (only requiring 1.25 GB of storage),an attacker requires more than 1 year. An attack requiring 2⁶⁴ pairswould require 5.84×10¹¹ years using a single chip, or 584 years if 1billion chips were used, making such an attack completely impractical interms of time (not to mention the storage requirements!).

With regards to K₁, it should be noted that the MinTicks variable onlyslows down an attacker and causes the attack to cost more since it doesnot stop an attacker using multiple System chips in parallel. HoweverMinTicks does make an attack on K₂ more difficult, since each consumablehas a different M (part of M is random read-only data). In order tolaunch a differential attack, minimally different inputs are required,and this can only be achieved with a single consumable (containing aneffectively constant part of M). Minimally different inputs require theattacker to use a single chip, and MinTicks causes the use of a singlechip to be slowed down. If it takes a year just to get the data to startsearching for values to begin a differential attack this increases thecost of attack and reduces the effective market time of a cloneconsumable.

Authentication Chip Commands

The System communicates with the Authentication Chips via a simpleoperation command set. This section details the actual commands andparameters necessary for implementation of Protocol 3. TheAuthentication Chip is defined here as communicating to System via aserial interface as a minimum implementation. It is a trivial matter todefine an equivalent chip that operates over a wider interface (such as8, 16 or 32 bits). Each command is defined by 3-bit opcode. Theinterpretation of the opcode can depend on the current value of theIsTrusted bit and the current value of the IsWritten bit. The followingoperations are defined:

Op T W Mn Input Output Description 000 — — CLR — — Clear 001 0 0 SSI[160, 160, 160] — Set Secret Information 010 0 1 RD [160, 160] [256,160] Read M securely 010 1 1 RND — [160, 160] Random 011 0 1 WR [256] —Write M 011 1 1 TST [256, 160] [1] Test 100 0 1 SAM [32] [32] Set AccessMode 101 — 1 GIT — [1] Get Is Trusted 110 — 1 SMT [32] — Set MinTicks Op= Opcode, T = IsTrusted value, W = IsWritten value, Mn = Mnemonic, [n] =number of bits required for parameter

Any command not defined in this table is interpreted as NOP (NoOperation). Examples include opcodes 110 and 111 (regardless ofIsTrusted or IsWritten values), and any opcode other than SSI whenIsWritten=0. Note that the opcodes for RD and RND are the same, as arethe opcodes for WR and TST. The actual command run upon receipt of theopcode will depend on the current value of the IsTrusted bit (as long asIsWritten is 1). Where the IsTrusted bit is clear, RD and WR functionswill be called. Where the IsTrusted bit is set, RND and TST functionswill be called. The two sets of commands are mutually exclusive betweentrusted and non-trusted Authentication Chips, and the same opcodesenforces this relationship. Each of the commands is examined in detailin the subsequent sections. Note that some algorithms are specificallydesigned because Flash memory is assumed for the implementation ofnon-volatile variables.

CLR Clear Input None Output None Changes All

The CLR (Clear) Command is designed to completely erase the contents ofall Authentication Chip memory. This includes all keys and secretinformation, access mode bits, and state data. After the execution ofthe CLR command, an Authentication Chip will be in a programmable state,just as if it had been freshly manufactured. It can be reprogrammed witha new key and reused. A CLR command consists of simply the CLR commandopcode. Since the Authentication Chip is serial, this must betransferred one bit at a time. The bit order is LSB to MSB for eachcommand component. A CLR command is therefore sent as bits 0-2 of theCLR opcode. A total of 3 bits are transferred. The CLR command can becalled directly at any time. The order of erasure is important.SIWritten must be cleared first, to disable further calls to key accessfunctions (such as RND, TST, RD and WR). If the AccessMode bits arecleared before SIWritten, an attacker could remove power at some pointafter they have been cleared, and manipulate M, thereby have a betterchance of retrieving the secret information with a partial chosen textattack. The CLR command is implemented with the following steps:

Step Action 1 Erase SIWritten Erase IsTrusted Erase K₁ Erase K₂ Erase RErase M 2 Erase AccessMode Erase MinTicks

Once the chip has been cleared it is ready for reprogramming and reuse.A blank chip is of no use to an attacker, since although they can createany value for M (M can be read from and written to), key-based functionswill not provide any information as K₁ and K₂ will be incorrect. It isnot necessary to consume any input parameter bits if CLR is called forany opcode other than CLR. An attacker will simply have to RESET thechip. The reason for calling CLR is to ensure that all secretinformation has been destroyed, making the chip useless to an attacker.

SSI—Set Secret Information

Input: K₁, K₂, R=[160 bits, 160 bits, 160 bits]

Output: None Changes: K₁, K₂, R, SIWritten, IsTrusted

The SSI (Set Secret Information) command is used to load the K₁, K₂ andR variables, and to set SIWritten and IsTrusted flags for later calls toRND, TST, RD and WR commands. An SSI command consists of the SSI commandopcode followed by the secret information to be stored in the K₁, K₂ andR registers. Since the Authentication Chip is serial, this must betransferred one bit at a time. The bit order is LSB to MSB for eachcommand component. An SSI command is therefore sent as: bits 0-2 of theSSI opcode, followed by bits 0-159 of the new value for K₁, bits 0-159of the new value for K₂, and finally bits 0-159 of the seed value for R.A total of 483 bits are transferred. The K₁, K₂, R, SIWritten, andIsTrusted registers are all cleared to 0 with a CLR command. They canonly be set using the SSI command.

The SSI command uses the flag SIWritten to store the fact that data hasbeen loaded into K₁, K₂, and R. If the SIWritten and IsTrusted flags areclear (this is the case after a CLR instruction), then K₁, K₂ and R areloaded with the new values. If either flag is set, an attempted call toSSI results in a CLR command being executed, since only an attacker oran erroneous client would attempt to change keys or the random seedwithout calling CLR first. The SSI command also sets the IsTrusted flagdepending on the value for R. If R=0, then the chip is considereduntrustworthy, and therefore IsTrusted remains at 0. If R≠0, then thechip is considered trustworthy, and therefore IsTrusted is set to 1.Note that the setting of the IsTrusted bit only occurs during the SSIcommand. If an Authentication Chip is to be reused, the CLR command mustbe called first. The keys can then be safely reprogrammed with an SSIcommand, and fresh state information loaded into M using the SAM and WRcommands. The SSI command is implemented with the following steps:

Step Action 1 CLR 2 K₁ ← Read 160 bits from client 3 K₂ ← Read 160 bitsfrom client 4 R ← Read 160 bits from client 5 IF (R ≠ 0) IsTrusted ← 1 6SIWritten ← 1

RD—Read

Input: X, F_(K1)[X]=[160 bits, 160 bits]Output: M, F_(K2)[X|M]=[256 bits, 160 bits]

Changes: R

The RD (Read) command is used to securely read the entire 256 bits ofstate data (M) from a non-trusted Authentication Chip. Only a validAuthentication Chip will respond correctly to the RD request. The outputbits from the RD command can be fed as the input bits to the TST commandon a trusted Authentication Chip for verification, with the first 256bits (M) stored for later use if (as we hope) TST returns 1. Since theAuthentication Chip is serial, the command and input parameters must betransferred one bit at a time. The bit order is LSB to MSB for eachcommand component. A RD command is therefore: bits 0-2 of the RD opcode,followed by bits 0-159 of X, and bits 0-159 of F_(K1)[X]. 323 bits aretransferred in total. X and F_(K1)[X] are obtained by calling thetrusted Authentication Chip's RND command. The 320 bits output by thetrusted chip's RND command can therefore be fed directly into thenon-trusted chip's RD command, with no need for these bits to be storedby System. The RD command can only be used when the following conditionshave been met:

-   -   SIWritten=1 indicating that K₁, K₂ and R have been set up via        the SSI command; and    -   IsTrusted=0 indicating the chip is not trusted since it is not        permitted to generate random number sequences;

In addition, calls to RD must wait for the MinTicksRemaining register toreach 0. Once it has done so, the register is reloaded with MinTicks toensure that a minimum time will elapse between calls to RD. OnceMinTicksRemaining has been reloaded with MinTicks, the RD commandverifies that the input parameters are valid. This is accomplished byinternally generating F_(K1)[X] for the input X, and then comparing theresult against the input F_(K1)[X]. This generation and comparison musttake the same amount of time regardless of whether the input parametersare correct or not. If the times are not the same, an attacker can gaininformation about which bits of F_(K1)[X] are incorrect. The only wayfor the input parameters to be invalid is an erroneous System (passingthe wrong bits), a case of the wrong consumable in the wrong System, abad trusted chip (generating bad pairs), or an attack on theAuthentication Chip. A constant value of 0 is returned when the inputparameters are wrong. The time taken for 0 to be returned must be thesame for all bad inputs so that attackers can learn nothing about whatwas invalid. Once the input parameters have been verified the outputvalues are calculated. The 256 bit content of M are transferred in thefollowing order: bits 0-15 of M[0], bits 0-15 of M[1], through to bits0-15 of M[15]. F_(K2)[X|M] is calculated and output as bits 0-159. The Rregister is used to store the X value during the validation of the X,F_(K1)[X] pair. This is because RND and RD are mutually exclusive. TheRD command is implemented with the following steps:

Step Action 1 IF (MinTicksRemaining ≠ 0 GOTO 1 2 MinTicksRemaining ←MinTicks 3 R ← Read 160 bits from client 4 Hash ← Calculate F_(K1)[R] 5OK ← (Hash = next 160 bits from client) Note that this operation musttake constant time so an attacker cannot determine how much of theirguess is correct. 6 IF (OK) Output 256 bits of M to client ELSE Output256 bits of 0 to client 7 Hash ← Calculate F_(K2)[R | M] 8 IF (OK)Output 160 bits of Hash to client ELSE Output 160 bits of 0 to client

RND—Random Input: None

Output: R, F_(K1)[R]=[160 bits, 160 bits]

Changes: None

The RND (Random) command is used by a client to obtain a valid R,F_(K1)[R] pair for use in a subsequent authentication via the RD and TSTcommands. Since there are no input parameters, an RND command istherefore simply bits 0-2 of the RND opcode. The RND command can only beused when the following conditions have been met:

-   -   SIWritten=1 indicating K₁ and R have been set up via the SSI        command;    -   IsTrusted=1 indicating the chip is permitted to generate random        number sequences;

RND returns both R and F_(K1)[R] to the caller. The 288-bit output ofthe RND command can be fed straight into the non-trusted chip's RDcommand as the input parameters. There is no need for the client tostore them at all, since they are not required again. However the TSTcommand will only succeed if the random number passed into the RDcommand was obtained first from the RND command. If a caller only callsRND multiple times, the same R, F_(K1)[R] pair will be returned eachtime. R will only advance to the next random number in the sequenceafter a successful call to TST. See TST for more information. The RNDcommand is implemented with the following steps:

Step Action 1 Output 160 bits of R to client 2 Hash ← CalculateF_(K1)[R] 3 Output 160 bits of Hash to client

TST—Test

Input: X, F_(K2)[R|X]=[256 bits, 160 bits]Output: 1 or 0=[1 bit]Changes: M, R and MinTicksRemaining (or all registers if attackdetected)

The TST (Test) command is used to authenticate a read of M from anon-trusted Authentication Chip. The TST (Test) command consists of theTST command opcode followed by input parameters: X and F_(K2)[R|X].Since the Authentication Chip is serial, this must be transferred onebit at a time. The bit order is LSB to MSB for each command component. ATST command is therefore: bits 0-2 of the TST opcode, followed by bits0-255 of M, bits 0-159 of F_(K2)[R|M]. 419 bits are transferred intotal. Since the last 416 input bits are obtained as the output bitsfrom a RD command to a non-trusted Authentication Chip, the entire datadoes not even have to be stored by the client. Instead, the bits can bepassed directly to the trusted Authentication Chip's TST command. Onlythe 256 bits of M should be kept from a RD command. The TST command canonly be used when the following conditions have been met:

-   -   SIWritten=1 indicating K₂ and R have been set up via the SSI        command;    -   IsTrusted=1 indicating the chip is permitted to generate random        number sequences;

In addition, calls to TST must wait for the MinTicksRemaining registerto reach 0. Once it has done so, the register is reloaded with MinTicksto ensure that a minimum time will elapse between calls to TST. TSTcauses the internal M value to be replaced by the input M value.F_(K2)[M|R] is then calculated, and compared against the 160 bit inputhash value. A single output bit is produced: 1 if they are the same, and0 if they are different. The use of the internal M value is to savespace on chip, and is the reason why RD and TST are mutually exclusivecommands. If the output bit is 1, R is updated to be the next randomnumber in the sequence. This forces the caller to use a new randomnumber each time RD and TST are called. The resultant output bit is notoutput until the entire input string has been compared, so that the timeto evaluate the comparison in the TST function is always the same. Thusno attacker can compare execution times or number of bits processedbefore an output is given.

The next random number is generated from R using a 160-bit maximalperiod LFSR (tap selections on bits 159, 4, 2, and 1). The initial160-bit value for R is set up via the SSI command, and can be any randomnumber except 0 (an LFSR filled with 0s will produce a never-endingstream of 0s). R is transformed by XORing bits 1, 2, 4, and 159together, and shifting all 160 bits right 1 bit using the XOR result asthe input bit to b₁₅₉. The new R will be returned on the next call toRND. Note that the time taken for 0 to be returned from TST must be thesame for all bad inputs so that attackers can learn nothing about whatwas invalid about the input.

The TST command is implemented with the following steps:

Step Action 1 IF (MinTicksRemaining ≠ 0 GOTO 1 2 MinTicksRemaining ←MinTicks 3 M ← Read 256 bits from client 4 IF (R = 0) GOTO CLR 5 Hash ←Calculate F_(K2)[R | M] 6 OK ← (Hash = next 160 bits from client) Notethat this operation must take constant time so an attacker cannotdetermine how much of their guess is correct. 7 IF (OK) Temp ← R Erase RAdvance TEMP via LFSR R ← TEMP 8 Output 1 bit of OK to client

Note that we can't simply advance R directly in Step 7 since R is Flashmemory, and must be erased in order for any set bit to become 0. Ifpower is removed from the Authentication Chip during Step 7 aftererasing the old value of R, but before the new value for R has beenwritten, then R will be erased but not reprogrammed. We therefore havethe situation of IsTrusted=1, yet R=0, a situation only possible due toan attacker. Step 4 detects this event, and takes action if the attackis detected.

This problem can be avoided by having a second 160-bit Flash registerfor R and a Validity Bit, toggled after the new value has been loaded.It has not been included in this implementation for reasons of space,but if chip space allows it, an extra 160-bit Flash register would beuseful for this purpose.

WR—Write

Input: M_(new)=[256 bits]

Output: None Changes: M

A WR (Write) command is used to update the writeable parts of Mcontaining Authentication Chip state data. The WR command by itself isnot secure. It must be followed by an authenticated read of M (via a RDcommand) to ensure that the change was made as specified. The WR commandis called by passing the WR command opcode followed by the new 256 bitsof data to be written to M. Since the Authentication Chip is serial, thenew value for M must be transferred one bit at a time. The bit order isLSB to MSB for each command component. A WR command is therefore: bits0-2 of the WR opcode, followed by bits 0-15 of M[0], bits 0-15 of M[1],through to bits 0-15 of M[15]. 259 bits are transferred in total. The WRcommand can only be used when SIWritten=1, indicating that K₁, K₂ and Rhave been set up via the SSI command (if SIWritten is 0, then K₁, K₂ andR have not been setup yet, and the CLR command is called instead). Theability to write to a specific M[n] is governed by the correspondingAccess Mode bits as stored in the AccessMode register. The AccessModebits can be set using the SAM command. When writing the new value toM[n] the fact that M[n] is Flash memory must be taken into account. Allthe bits of M[n] must be erased, and then the appropriate bits set.Since these two steps occur on different cycles, it leaves thepossibility of attack open. An attacker can remove power after erasure,but before programming with the new value. However, there is noadvantage to an attacker in doing this:

-   -   A Read/Write M[n] changed to 0 by this means is of no advantage        since the attacker could have written any value using the WR        command anyway.    -   A Read Only M[n] changed to 0 by this means allows an additional        known text pair (where the M[n] is 0 instead of the original        value). For future use M[n] values, they are already 0, so no        information is given.    -   A Decrement Only M[n] changed to 0 simply speeds up the time in        which the consumable is used up. It does not give any new        information to an attacker that using the consumable would give.

The WR command is implemented with the following steps:

Step Action  1 DecEncountered ← 0 EqEncountered ← 0 n ← 15  2 Temp ←Read 16 bits from client  3 AM = AccessMode[~n] Compare to the previousvalue  5 LT ← (Temp < M[~n]) [comparison is unsigned] EQ ← (Temp =M[~n])  6 WE ← (AM = RW) 

((AM = MSR)

 LT) 

((AM = NMSR)

 (DecEncountered

 LT))  7 DecEncountered ← ((AM = MSR)

 LT) 

((AM = NMSR)

 DecEncountered) 

((AM = NMSR)

 EqEncountered

 LT) EqEncountered ← ((AM = MSR)

 EQ) 

((AM = NMSR)

 EqEncountered

 EQ) Advance to the next Access Mode set and write the new M[~n] ifapplicable  8 IF (WE) Erase M[~n] M[~n] ← Temp 10

n 11 IF (n ≠ 0) GOTO 2

SAM—Set AccessMode

Input: AccessMode_(new)=[32 bits]Output: AccessMode=[32 bits]

Changes: AccessMode

The SAM (Set Access Mode) command is used to set the 32 bits of theAccessMode register, and is only available for use in consumableAuthentication Chips (where the IsTrusted flag=0). The SAM command iscalled by passing the SAM command opcode followed by a 32-bit value thatis used to set bits in the AccessMode register. Since the AuthenticationChip is serial, the data must be transferred one bit at a time. The bitorder is LSB to MSB for each command component. A SAM command istherefore: bits 0-2 of the SAM opcode, followed by bits 0-31 of bits tobe set in AccessMode. 35 bits are transferred in total. The AccessModeregister is only cleared to 0 upon execution of a CLR command. Since anaccess mode of 00 indicates an access mode of RW (read/write), notsetting any AccessMode bits after a CLR means that all of M can be readfrom and written to. The SAM command only sets bits in the AccessModeregister. Consequently a client can change the access mode bits for M[n]from RW to RO (read only) by setting the appropriate bits in a 32-bitword, and calling SAM with that 32-bit value as the input parameter.This allows the programming of the access mode bits at different times,perhaps at different stages of the manufacturing process. For example,the read only random data can be written to during the initial keyprogramming stage, while allowing a second programming stage for itemssuch as consumable serial numbers.

Since the SAM command only sets bits, the effect is to allow the accessmode bits corresponding to M[n] to progress from RW to either MSR, NMSR,or RO. It should be noted that an access mode of MSR can be changed toRO, but this would not help an attacker, since the authentication of Mafter a write to a doctored Authentication Chip would detect that thewrite was not successful and hence abort the operation. The setting ofbits corresponds to the way that Flash memory works best. The only wayto clear bits in the AccessMode register, for example to change aDecrement Only M[n] to be Read/Write, is to use the CLR command. The CLRcommand not only erases (clears) the AccessMode register, but alsoclears the keys and all of M. Thus the AccessMode[n] bits correspondingto M[n] can only usefully be changed once between CLR commands. The SAMcommand returns the new value of the AccessMode register (after theappropriate bits have been set due to the input parameter). By callingSAM with an input parameter of 0, AccessMode will not be changed, andtherefore the current value of AccessMode will be returned to thecaller.

The SAM command is implemented with the following steps:

Step Action 1 Temp ← Read 32 bits from client 2 SetBits(AccessMode,Temp) 3 Output 32 bits of AccessMode to client

GIT—Get Is Trusted Input: None

Output: IsTrusted=[1 bit]

Changes: None

The GIT (Get Is Trusted) command is used to read the current value ofthe IsTrusted bit on the Authentication Chip. If the bit returned is 1,the Authentication Chip is a trusted System Authentication Chip. If thebit returned is 0, the Authentication Chip is a consumableAuthentication Chip. A GIT command consists of simply the GIT commandopcode. Since the Authentication Chip is serial, this must betransferred one bit at a time. The bit order is LSB to MSB for eachcommand in component. A GIT command is therefore sent as bits 0-2 of theGIT opcode. A total of 3 bits are transferred. The GIT command isimplemented with the following steps:

Step Action 1 Output IsTrusted bit to client

SMT—Set MinTicks

Input: MinTicks_(new)=[32 bits]

Output: None Changes: MinTicks

The SMT (Set MinTicks) command is used to set bits in the MinTicksregister and hence define the minimum number of ticks that must pass inbetween calls to TST and RD. The SMT command is called by passing theSMT command opcode followed by a 32-bit value that is used to set bitsin the MinTicks register. Since the Authentication Chip is serial, thedata must be transferred one bit at a time. The bit order is LSB to MSBfor each command component. An SMT command is therefore: bits 0-2 of theSMT opcode, followed by bits 0-31 of bits to be set in MinTicks. 35 bitsare transferred in total. The MinTicks register is only cleared to 0upon execution of a CLR command. A value of 0 indicates that no ticksneed to pass between calls to key-based functions. The functions maytherefore be called as frequently as the clock speed limiting hardwareallows the chip to run. Since the SMT command only sets bits, the effectis to allow a client to set a value, and only increase the time delay iffurther calls are made. Setting a bit that is already set has no effect,and setting a bit that is clear only serves to slow the chip downfurther. The setting of bits corresponds to the way that Flash memoryworks best. The only way to clear bits in the MinTicks register, forexample to change a value of 10 ticks to a value of 4 ticks, is to usethe CLR command. However the CLR command clears the MinTicks register to0 as well as clearing all keys and M. It is therefore useless for anattacker. Thus the MinTicks register can only usefully be changed oncebetween CLR commands.

The SMT command is implemented with the following steps:

Step Action 1 Temp ← Read 32 bits from client 2 SetBits(MinTicks, Temp)

Programming Authentication Chips

Authentication Chips must be programmed with logically secureinformation in a physically secure environment. Consequently theprogramming procedures cover both logical and physical security. Logicalsecurity is the process of ensuring that K₁, K₂, R, and the random M[n]values are generated by a physically random process, and not by acomputer. It is also the process of ensuring that the order in whichparts of the chip are programmed is the most logically secure. Physicalsecurity is the process of ensuring that the programming station isphysically secure, so that K₁ and K₂ remain secret, both during the keygeneration stage and during the lifetime of the storage of the keys. Inaddition, the programming station must be resistant to physical attemptsto obtain or destroy the keys. The Authentication Chip has its ownsecurity mechanisms for ensuring that K₁ and K₂ are kept secret, but theProgramming Station must also keep K₁ and K₂ safe.

Overview

After manufacture, an Authentication Chip must be programmed before itcan be used. In all chips values for K₁ and K₂ must be established. Ifthe chip is destined to be a System Authentication Chip, the initialvalue for R must be determined. If the chip is destined to be aconsumable Authentication Chip, R must be set to 0, and initial valuesfor M and AccessMode must be set up. The following stages are thereforeidentified:

-   -   Determine Interaction between Systems and Consumables    -   Determine Keys for Systems and Consumables    -   Determine MinTicks for Systems and Consumables    -   Program Keys, Random Seed, MinTicks and Unused M    -   Program State Data and Access Modes

Once the consumable or system is no longer required, the attachedAuthentication Chip can be reused. This is easily accomplished byreprogrammed the chip starting at Stage 4 again. Each of the stages isexamined in the subsequent sections.

Stage 0: Manufacture

The manufacture of Authentication Chips does not require any specialsecurity. There is no secret information programmed into the chips atmanufacturing stage. The algorithms and chip process is not special.Standard Flash processes are used. A theft of Authentication Chipsbetween the chip manufacturer and programming station would only providethe clone manufacturer with blank chips. This merely compromises thesale of Authentication chips, not anything authenticated byAuthentication Chips. Since the programming station is the onlymechanism with consumable and system product keys, a clone manufacturerwould not be able to program the chips with the correct key. Clonemanufacturers would be able to program the blank chips for their ownsystems and consumables, but it would be difficult to place these itemson the market without detection. In addition, a single theft would bedifficult to base a business around.

Stage 1: Determine Interaction Between Systems and Consumables

The decision of what is a System and what is a Consumable needs to bedetermined before any Authentication Chips can be programmed. A decisionneeds to be made about which Consumables can be used in which Systems,since all connected Systems and Consumables must share the same keyinformation. They also need to share state-data usage mechanisms even ifsome of the interpretations of that data have not yet been determined. Asimple example is that of a car and car-keys. The car itself is theSystem, and the car-keys are the consumables. There are several car-keysfor each car, each containing the same key information as the specificcar. However each car (System) would contain a different key (shared byits car-keys), since we don't want car-keys from one car working inanother. Another example is that of a photocopier that requires aparticular toner cartridge. In simple terms the photocopier is theSystem, and the toner cartridge is the consumable. However the decisionmust be made as to what compatibility there is to be between cartridgesand photocopiers. The decision has historically been made in terms ofthe physical packaging of the toner cartridge: certain cartridges willor won't fit in a new model photocopier based on the design decisionsfor that copier. When Authentication Chips are used, the components thatmust work together must share the same key information.

In addition, each type of consumable requires a different way ofdividing M (the state data). Although the way in which M is used willvary from application to application, the method of allocating M[n] andAccessMode[n] will be the same:

-   -   Define the consumable state data for specific use    -   Set some M[n] registers aside for future use (if required). Set        these to be 0 and Read Only. The value can be tested for in        Systems to maintain compatibility.    -   Set the remaining M[n] registers (at least one, but it does not        have to be M[15]) to be Read Only, with the contents of each        M[n] completely random. This is to make it more difficult for a        clone manufacturer to attack the authentication keys.

The following examples show ways in which the state data may beorganized.

Example 1

Suppose we have a car with associated car-keys. A 16-bit key number ismore than enough to uniquely identify each car-key for a given car. The256 bits of M could be divided up as follows:

M[n] Access Description 0 RO Key number (16 bits) 1-4 RO Car enginenumber (64 bits) 5-8 RO For future expansion = 0 (64 bits) 8-15 RORandom bit data (128 bits)

If the car manufacturer keeps all logical keys for all cars, it is atrivial matter to manufacture a new physical car-key for a given carshould one be lost. The new car-key would contain a new Key Number inM[0], but have the same K₁ and K₂ as the car's Authentication Chip. CarSystems could allow specific key numbers to be invalidated (for exampleif a key is lost). Such a system might require Key 0 (the master key) tobe inserted first, then all valid keys, then Key 0 again. Only thosevalid keys would now work with the car. In the worst case, for exampleif all car-keys are lost, then a new set of logical keys could begenerated for the car and its associated physical car-keys if desired.The Car engine number would be used to tie the key to the particularcar. Future use data may include such things as rental information, suchas driver/renter details.

Example 2

Suppose we have a photocopier image unit which should be replaced every100,000 copies. 32 bits are required to store the number of pagesremaining The 256 bits of M could be divided up as follows:

M[n] Access Description 0 RO Serial number (16 bits) 1 RO Batch number(16 bits) 2 MSR Page Count Remaining (32 bits, hi/lo) 3 NMSR 4-7 RO Forfuture expansion = 0 (64 bits) 8-15 RO Random bit data (128 bits)

If a lower quality image unit is made that must be replaced after only10,000 copies, the 32-bit page count can still be used for compatibilitywith existing photocopiers. This allows several consumable types to beused with the same system.

Example 3

Consider a Polaroid camera consumable containing 25 photos. A 16-bitcountdown is all that is required to store the number of photosremaining. The 256 bits of M could be divided up as follows:

M[n] Access Description 0 RO Serial number (16 bits) 1 RO Batch number(16 bits) 2 MSR Photos Remaining (16 bits) 3-6 RO For future expansion =0 (64 bits) 7-15 RO Random bit data (144 bits)

The Photos Remaining value at M[2] allows a number of consumable typesto be built for use with the same camera System. For example, a newconsumable with 36 photos is trivial to program. Suppose 2 years afterthe introduction of the camera, a new type of camera was introduced. Itis able to use the old consumable, but also can process a new film type.M[3] can be used to define Film Type. Old film types would be 0, and thenew film types would be some new value. New Systems can take advantageof this. Original systems would detect a non-zero value at M[3] andrealize incompatibility with new film types. New Systems wouldunderstand the value of M[3] and so react appropriately. To maintaincompatibility with the old consumable, the new consumable and Systemneeds to have the same key information as the old one. To make a cleanbreak with a new System and its own special consumables, a new key setwould be required.

Example 4

Consider a printer consumable containing 3 inks—cyan, magenta, andyellow. Each ink amount can be decremented separately. The 256 bits of Mcould be divided up as follows:

M[n] Access Description  0 RO Serial number (16 bits)  1 RO Batch number(16 bits)  2 MSR Cyan Remaining (32 bits, hi/lo)  3 NMSR  4 MSR MagentaRemaining (32 bits, hi/lo)  5 NMSR  6 MSR Yellow Remaining (32 bits,hi/lo)  7 NMSR  8-11 RO For future expansion = 0 (64 bits) 12-15 RORandom bit data (64 bits)

Stage 2: Determine Keys for Systems and Consumables

Once the decision has been made as to which Systems and consumables areto share the same keys, those keys must be defined. The values for K₁and K₂ must therefore be determined. In most cases, K₁ and K₂ will begenerated once for all time. All Systems and consumables that have towork together (both now and in the future) need to have the same K₁ andK₂ values. K₁ and K₂ must therefore be kept secret since the entiresecurity mechanism for the System/Consumable combination is made void ifthe keys are compromised. If the keys are compromised, the damagedepends on the number of systems and consumables, and the ease to whichthey can be reprogrammed with new non-compromised keys: In the case of aphotocopier with toner cartridges, the worst case is that a clonemanufacturer could then manufacture their own Authentication Chips (orworse, buy them), program the chips with the known keys, and then insertthem into their own consumables. In the case of a car with car-keys,each car has a different set of keys. This leads to two possible generalscenarios. The first is that after the car and car-keys are programmedwith the keys, K₁ and K₂ are deleted so no record of their values arekept, meaning that there is no way to compromise K₁ and K₂. However nomore car-keys can be made for that car without reprogramming the car'sAuthentication Chip. The second scenario is that the car manufacturerkeeps K₁ and K₂, and new keys can be made for the car. A compromise ofK₁ and K₂ means that someone could make a car-key specifically for aparticular car.

The keys and random data used in the Authentication Chips must thereforebe generated by a means that is non-deterministic (a completely computergenerated pseudo-random number cannot be used because it isdeterministic—knowledge of the generator's seed gives all futurenumbers). K₁ and K₂ should be generated by a physically random process,and not by a computer. However, random bit generators based on naturalsources of randomness are subject to influence by external factors andalso to malfunction. It is imperative that such devices be testedperiodically for statistical randomness.

A simple yet useful source of random numbers is the Lavarand® systemfrom SGI. This generator uses a digital camera to photograph six lavalamps every few minutes. Lava lamps contain chaotic turbulent systems.The resultant digital images are fed into an SHA-1 implementation thatproduces a 7-way hash, resulting in a 160-bit value from every 7th byefrom the digitized image. These 7 sets of 160 bits total 140 bytes. The140 byte value is fed into a BBS generator to position the start of theoutput bitstream. The output 160 bits from the BBS would be the key orthe Authentication chip 53. An extreme example of a non-deterministicrandom process is someone flipping a coin 160 times for K₁ and 160 timesfor K₂ in a clean room. With each head or tail, a 1 or 0 is entered on apanel of a Key Programmer Device. The process must be undertaken withseveral observers (for verification) in silence (someone may have ahidden microphone). The point to be made is that secure data entry andstorage is not as simple as it sounds. The physical security of the KeyProgrammer Device and accompanying Programming Station requires anentire document of its own. Once keys K₁ and K₂ have been determined,they must be kept for as long as Authentication Chips need to be madethat use the key. In the first car/car-key scenario K₁ and K₂ aredestroyed after a single System chip and a few consumable chips havebeen programmed. In the case of the photocopier/toner cartridge, K₁ andK₂ must be retained for as long as the toner-cartridges are being madefor the photocopiers. The keys must be kept securely.

Stage 3: Determine MinTicks for Systems and Consumables

The value of MinTicks depends on the operating clock speed of theAuthentication Chip (System specific) and the notion of what constitutesa reasonable time between RD or TST function calls (applicationspecific). The duration of a single tick depends on the operating clockspeed. This is the maximum of the input clock speed and theAuthentication Chip's clock-limiting hardware. For example, theAuthentication Chip's clock-limiting hardware may be set at 10 MHz (itis not changeable), but the input clock is 1 MHz. In this case, thevalue of 1 tick is based on 1 MHz, not 10 MHz. If the input clock was 20MHz instead of 1 MHz, the value of 1 tick is based on 10 MHz (since theclock speed is limited to 10 MHz). Once the duration of a tick is known,the MinTicks value can be set. The value for MinTicks is the minimumnumber of ticks required to pass between calls to RD or RND key-basedfunctions. Suppose the input clock speed matches the maximum clock speedof 10 MHz. If we want a minimum of 1 second between calls to TST, thevalue for MinTicks is set to 10,000,000. Even a value such as 2 secondsmight be a completely reasonable value for a System such as a printer(one authentication per page, and one page produced every 2 or 3seconds).

Stage 4: Program Keys, Random Seed, MinTicks and Unused M

Authentication Chips are in an unknown state after manufacture.Alternatively, they have already been used in one consumable, and mustbe reprogrammed for use in another. Each Authentication Chip must becleared and programmed with new keys and new state data. Clearing andsubsequent programming of Authentication Chips must take place in asecure Programming Station environment.

Programming a Trusted System Authentication Chip

If the chip is to be a trusted System chip, a seed value for R must begenerated. It must be a random number derived from a physically randomprocess, and must not be 0. The following tasks must be undertaken, inthe following order, and in a secure programming environment:

-   -   RESET the chip    -   CLR[ ]    -   Load R (160 bit register) with physically random data    -   SSI[K₁, K₂, R]    -   SMT[MinTicks_(system)]

The Authentication Chip is now ready for insertion into a System. It hasbeen completely programmed. If the System Authentication Chips arestolen at this point, a clone manufacturer could use them to generate R,F_(K1)[R] pairs in order to launch a known text attack on K₁, or to usefor launching a partially chosen-text attack on K₂. This is no differentto the purchase of a number of Systems, each containing a trustedAuthentication Chip. The security relies on the strength of theAuthentication protocols and the randomness of K₁ and K₂.

Programming a Non-Trusted Consumable Authentication Chip

If the chip is to be a non-trusted Consumable Authentication Chip, theprogramming is slightly different to that of the trusted SystemAuthentication Chip. Firstly, the seed value for R must be 0. It musthave additional programming for M and the AccessMode values. The futureuse M[n] must be programmed with 0, and the random M[n] must beprogrammed with random data. The following tasks must be undertaken, inthe following order, and in a secure programming environment:

-   -   RESET the chip    -   CLR[ ]    -   Load R (160 bit register) with 0    -   SSI[K₁, K₂, R]    -   Load X (256 bit register) with 0    -   Set bits in X corresponding to appropriate M[n] with physically        random data    -   WR[X]    -   Load Y (32 bit register) with 0    -   Set bits in Y corresponding to appropriate M[n] with Read Only        Access Modes    -   SAM[Y]    -   SMT[MinTicks_(consumable)]

The non-trusted consumable chip is now ready to be programmed with thegeneral state data. If the Authentication Chips are stolen at thispoint, an attacker could perform a limited chosen text attack. In thebest situation, parts of M are Read Only (0 and random data), with theremainder of M completely chosen by an attacker (via the WR command). Anumber of RD calls by an attacker obtains F_(K2)[M|R] for a limited M.In the worst situation, M can be completely chosen by an attacker (sinceall 256 bits are used for state data). In both cases however, theattacker cannot choose any value for R since it is supplied by calls toRND from a System Authentication Chip. The only way to obtain a chosen Ris by a Brute Force attack. It should be noted that if Stages 4 and 5are carried out on the same Programming Station (the preferred and idealsituation), Authentication Chips cannot be removed in between thestages. Hence there is no possibility of the Authentication Chips beingstolen at this point. The decision to program the Authentication Chipsat one or two times depends on the requirements of the System/Consumablemanufacturer.

Stage 5: Program State Data and Access Modes

This stage is only required for consumable Authentication Chips, since Mand AccessMode registers cannot be altered on System AuthenticationChips. The future use and random values of M[n] have already beenprogrammed in Stage 4. The remaining state data values need to beprogrammed and the associated Access Mode values need to be set. Bear inmind that the speed of this stage will be limited by the value stored inthe MinTicks register. This stage is separated from Stage 4 on accountof the differences either in physical location or in time betweenwhere/when Stage 4 is performed, and where/when Stage 5 is performed.Ideally, Stages 4 and 5 are performed at the same time in the sameProgramming Station. Stage 4 produces valid Authentication Chips, butdoes not load them with initial state values (other than 0). This is toallow the programming of the chips to coincide with production line runsof consumables. Although Stage 5 can be run multiple times, each timesetting a different state data value and Access Mode value, it is morelikely to be run a single time, setting all the remaining state datavalues and setting all the remaining Access Mode values. For example, aproduction line can be set up where the batch number and serial numberof the Authentication Chip is produced according to the physicalconsumable being produced. This is much harder to match if the statedata is loaded at a physically different factory.

The Stage 5 process involves first checking to ensure the chip is avalid consumable chip, which includes a RD to gather the data from theAuthentication Chip, followed by a WR of the initial data values, andthen a SAM to permanently set the new data values. The steps areoutlined here:

-   -   IsTrusted=GIT[ ]    -   If (IsTrusted), exit with error (wrong kind of chip!)    -   Call RND on a valid System chip to get a valid input pair    -   Call RD on chip to be programmed, passing in valid input pair    -   Load X (256 bit register) with results from a RD of        Authentication Chip    -   Call TST on valid System chip to ensure X and consumable chip        are valid    -   If (TST returns 0), exit with error (wrong consumable chip for        system)    -   Set bits of X to initial state values    -   WR[X]    -   Load Y (32 bit register) with 0    -   Set bits of Y corresponding to Access Modes for new state values    -   SAM[Y]

Of course the validation (Steps 1 to 7) does not have to occur if Stage4 and 5 follow on from one another on the same Programming Station. Butit should occur in all other situations where Stage 5 is run as aseparate programming process from Stage 4. If these Authentication Chipsare now stolen, they are already programmed for use in a particularconsumable. An attacker could place the stolen chips into a cloneconsumable. Such a theft would limit the number of cloned products tothe number of chips stolen. A single theft should not create a supplyconstant enough to provide clone manufacturers with a cost-effectivebusiness. The alternative use for the chips is to save the attacker frompurchasing the same number of consumables, each with an AuthenticationChip, in order to launch a partially chosen text attack or brute forceattack. There is no special security breach of the keys if such anattack were to occur.

Manufacture

The circuitry of the Authentication Chip must be resistant to physicalattack. A summary of manufacturing implementation guidelines ispresented, followed by specification of the chip's physical defenses(ordered by attack).

Guidelines for Manufacturing

The following are general guidelines for implementation of anAuthentication Chip in terms of manufacture:

-   -   Standard process    -   Minimum size (if possible)    -   Clock Filter    -   Noise Generator    -   Tamper Prevention and Detection circuitry    -   Protected memory with tamper detection    -   Boot circuitry for loading program code    -   Special implementation of FETs for key data paths    -   Data connections in polysilicon layers where possible    -   OverUnderPower Detection Unit    -   No test circuitry

Standard Process

The Authentication Chip should be implemented with a standardmanufacturing process (such as Flash). This is necessary to:

-   -   Allow a great range of manufacturing location options    -   Take advantage of well-defined and well-known technology    -   Reduce cost

Note that the standard process still allows physical protectionmechanisms.

Minimum Size

The Authentication chip 53 must have a low manufacturing cost in orderto be included as the authentication mechanism for low cost consumables.It is therefore desirable to keep the chip size as low as reasonablypossible. Each Authentication Chip requires 802 bits of non-volatilememory. In addition, the storage required for optimized HMAC-SHA1 is1024 bits. The remainder of the chip (state machine, processor, CPU orwhatever is chosen to implement Protocol 3) must be kept to a minimum inorder that the number of transistors is minimized and thus the cost perchip is minimized. The circuit areas that process the secret keyinformation or could reveal information about the key should also beminimized (see Non-Flashing CMOS below for special data paths).

Clock Filter

The Authentication Chip circuitry is designed to operate within aspecific clock speed range. Since the user directly supplies the clocksignal, it is possible for an attacker to attempt to introducerace-conditions in the circuitry at specific times during processing. Anexample of this is where a high clock speed (higher than the circuitryis designed for) may prevent an XOR from working properly, and of thetwo inputs, the first may always be returned. These styles of transientfault attacks can be very efficient at recovering secret keyinformation. The lesson to be learned from this is that the input clocksignal cannot be trusted. Since the input clock signal cannot betrusted, it must be limited to operate up to a maximum frequency. Thiscan be achieved a number of ways. One way to filter the clock signal isto use an edge detect unit passing the edge on to a delay, which in turnenables the input clock signal to pass through. FIG. 174 shows clocksignal flow within the Clock Filter. The delay should be set so that themaximum clock speed is a particular frequency (e.g. about 4 MHz). Notethat this delay is not programmable—it is fixed. The filtered clocksignal would be further divided internally as required.

Noise Generator

Each Authentication Chip should contain a noise generator that generatescontinuous circuit noise. The noise will interfere with otherelectromagnetic emissions from the chip's regular activities and addnoise to the I_(dd) signal. Placement of the noise generator is not anissue on an Authentication Chip due to the length of the emissionwavelengths. The noise generator is used to generate electronic noise,multiple state changes each clock cycle, and as a source ofpseudo-random bits for the Tamper Prevention and Detection circuitry. Asimple implementation of a noise generator is a 64-bit LFSR seeded witha non-zero number. The clock used for the noise generator should berunning at the maximum clock rate for the chip in order to generate asmuch noise as possible.

Tamper Prevention and Detection Circuitry

A set of circuits is required to test for and prevent physical attackson the Authentication Chip. However what is actually detected as anattack may not be an intentional physical attack. It is thereforeimportant to distinguish between these two types of attacks in anAuthentication Chip:

-   -   where you can be certain that a physical attack has occurred.    -   where you cannot be certain that a physical attack has occurred.

The two types of detection differ in what is performed as a result ofthe detection. In the first case, where the circuitry can be certainthat a true physical attack has occurred, erasure of Flash memory keyinformation is a sensible action. In the second case, where thecircuitry cannot be sure if an attack has occurred, there is stillcertainly something wrong. Action must be taken, but the action shouldnot be the erasure of secret key information. A suitable action to takein the second case is a chip RESET. If what was detected was an attackthat has permanently damaged the chip, the same conditions will occurnext time and the chip will RESET again. If, on the other hand, what wasdetected was part of the normal operating environment of the chip, aRESET will not harm the key. A good example of an event that circuitrycannot have knowledge about, is a power glitch. The glitch may be anintentional attack, attempting to reveal information about the key. Itmay, however, be the result of a faulty connection, or simply the startof a power-down sequence. It is therefore best to only RESET the chip,and not erase the key. If the chip was powering down, nothing is lost.If the System is faulty, repeated RESETs will cause the consumer to getthe System repaired. In both cases the consumable is still intact. Agood example of an event that circuitry can have knowledge about, is thecutting of a data line within the chip. If this attack is somehowdetected, it could only be a result of a faulty chip (manufacturingdefect) or an attack. In either case, the erasure of the secretinformation is a sensible step to take.

Consequently each Authentication Chip should have 2 Tamper DetectionLines as illustrated in Fig.—one for definite attacks, and one forpossible attacks. Connected to these Tamper Detection Lines would be anumber of Tamper Detection test units, each testing for different formsof tampering. In addition, we want to ensure that the Tamper DetectionLines and Circuits themselves cannot also be tampered with.

At one end of the Tamper Detection Line is a source of pseudo-randombits (clocking at high speed compared to the general operatingcircuitry). The Noise Generator circuit described above is an adequatesource. The generated bits pass through two different paths—one carriesthe original data, and the other carries the inverse of the data. Thewires carrying these bits are in the layer above the general chipcircuitry (for example, the memory, the key manipulation circuitry etc).The wires must also cover the random bit generator. The bits arerecombined at a number of places via an XOR gate. If the bits aredifferent (they should be), a 1 is output, and used by the particularunit (for example, each output bit from a memory read should be ANDedwith this bit value). The lines finally come together at the Flashmemory Erase circuit, where a complete erasure is triggered by a 0 fromthe XOR. Attached to the line is a number of triggers, each detecting aphysical attack on the chip. Each trigger has an oversize nMOStransistor attached to GND. The Tamper Detection Line physically goesthrough this nMOS transistor. If the test fails, the trigger causes theTamper Detect Line to become 0. The XOR test will therefore fail oneither this clock cycle or the next one (on average), thus RESETing orerasing the chip. FIG. 175 illustrates the basic principle of a TamperDetection Line in terms of tests and the XOR connected to either theErase or RESET circuitry. The Tamper Detection Line must go through thedrain of an output transistor for each test, as illustrated by theoversize nMOS transistor layout of FIG. 176. It is not possible to breakthe Tamper Detect Line since this would stop the flow of 1s and 0s fromthe random source. The XOR tests would therefore fail. As the TamperDetect Line physically passes through each test, it is not possible toeliminate any particular test without breaking the Tamper Detect Line.It is important that the XORs take values from a variety of places alongthe Tamper Detect Lines in order to reduce the chances of an attack.FIG. 177 illustrates the taking of multiple XORs from the Tamper DetectLine to be used in the different parts of the chip. Each of these XORscan be considered to be generating a ChipOK bit that can be used withineach unit or sub-unit.

A sample usage would be to have an OK bit in each unit that is ANDedwith a given ChipOK bit each cycle. The OK bit is loaded with 1 on aRESET. If OK is 0, that unit will fail until the next RESET. If theTamper Detect Line is functioning correctly, the chip will either RESETor erase all key information. If the RESET or erase circuitry has beendestroyed, then this unit will not function, thus thwarting an attacker.The destination of the RESET and Erase line and associated circuitry isvery context sensitive. It needs to be protected in much the same way asthe individual tamper tests. There is no point generating a RESET pulseif the attacker can simply cut the wire leading to the RESET circuitry.The actual implementation will depend very much on what is to be clearedat RESET, and how those items are cleared. Finally, FIG. 178 shows howthe Tamper Lines cover the noise generator circuitry of the chip. Thegenerator and NOT gate are on one level, while the Tamper Detect Linesrun on a level above the generator.

Protected Memory with Tamper Detection

It is not enough to simply store secret information or program code inFlash memory. The Flash memory and RAM must be protected from anattacker who would attempt to modify (or set) a particular bit ofprogram code or key information. The mechanism used must conform tobeing used in the Tamper Detection Circuitry (described above). Thefirst part of the solution is to ensure that the Tamper Detection Linepasses directly above each Flash or RAM bit. This ensures that anattacker cannot probe the contents of Flash or RAM. A breach of thecovering wire is a break in the Tamper Detection Line. The breach causesthe Erase signal to be set, thus deleting any contents of the memory.The high frequency noise on the Tamper Detection Line also obscurespassive observation.

The second part of the solution for Flash is to use multi-level datastorage, but only to use a subset of those multiple levels for valid bitrepresentations. Normally, when multi-level Flash storage is used, asingle floating gate holds more than one bit. For example, a4-voltage-state transistor can represent two bits. Assuming a minimumand maximum voltage representing 00 and 11 respectively, the two middlevoltages represent 01 and 10. In the Authentication Chip, we can use thetwo middle voltages to represent a single bit, and consider the twoextremes to be invalid states. If an attacker attempts to force thestate of a bit one way or the other by closing or cutting the gate'scircuit, an invalid voltage (and hence invalid state) results.

The second part of the solution for RAM is to use a parity bit. The datapart of the register can be checked against the parity bit (which willnot match after an attack). The bits coming from Flash and RAM cantherefore be validated by a number of test units (one per bit) connectedto the common Tamper Detection Line. The Tamper Detection circuitrywould be the first circuitry the data passes through (thus stopping anattacker from cutting the data lines).

Boot Circuitry for Loading Program Code

Program code should be kept in multi-level Flash instead of ROM, sinceROM is subject to being altered in a non-testable way. A boot mechanismis therefore required to load the program code into Flash memory (Flashmemory is in an indeterminate state after manufacture). The bootcircuitry must not be in ROM—a small state-machine would suffice.Otherwise the boot code could be modified in an undetectable way. Theboot circuitry must erase all Flash memory, check to ensure the erasureworked, and then load the program code. Flash memory must be erasedbefore loading the program code. Otherwise an attacker could put thechip into the boot state, and then load program code that simplyextracted the existing keys. The state machine must also check to ensurethat all Flash memory has been cleared (to ensure that an attacker hasnot cut the Erase line) before loading the new program code. The loadingof program code must be undertaken by the secure Programming Stationbefore secret information (such as keys) can be loaded.

Special Implementation of FETs for Key Data Paths

The normal situation for FET implementation for the case of a CMOSInverter (which involves a pMOS transistor combined with an nMOStransistor) is shown in FIG. 179. During the transition, there is asmall period of time where both the nMOS transistor and the pMOStransistor have an intermediate resistance. The resultant power-groundshort circuit causes a temporary increase in the current, and in factaccounts for the majority of current consumed by a CMOS device. A smallamount of infrared light is emitted during the short circuit, and can beviewed through the silicon substrate (silicon is transparent to infraredlight). A small amount of light is also emitted during the charging anddischarging of the transistor gate capacitance and transmission linecapacitance. For circuitry that manipulates secret key information, suchinformation must be kept hidden. An alternative non-flashing CMOSimplementation should therefore be used for all data paths thatmanipulate the key or a partially calculated value that is based on thekey. The use of two non-overlapping clocks φ1 and φ2 can provide anon-flashing mechanism. φ1 is connected to a second gate of all nMOStransistors, and φ2 is connected to a second gate of all pMOStransistors. The transition can only take place in combination with theclock. Since φ1 and φ2 are non-overlapping, the pMOS and nMOStransistors will not have a simultaneous intermediate resistance. Thesetup is shown in FIG. 180.

Finally, regular CMOS inverters can be positioned near criticalnon-Flashing CMOS components. These inverters should take their inputsignal from the Tamper Detection Line above. Since the Tamper DetectionLine operates multiple times faster than the regular operatingcircuitry, the net effect will be a high rate of light-bursts next toeach non-Flashing CMOS component. Since a bright light overwhelmsobservation of a nearby faint light, an observer will not be able todetect what switching operations are occurring in the chip proper. Theseregular CMOS inverters will also effectively increase the amount ofcircuit noise, reducing the SNR and obscuring useful EMI. There are anumber of side effects due to the use of non-Flashing CMOS:

-   -   The effective speed of the chip is reduced by twice the rise        time of the clock per clock cycle. This is not a problem for an        Authentication Chip.    -   The amount of current drawn by the non-Flashing CMOS is reduced        (since the short circuits do not occur). However, this is offset        by the use of regular CMOS inverters.    -   Routing of the clocks increases chip area, especially since        multiple versions of φ1 and φ2 are required to cater for        different levels of propagation. The estimation of chip area is        double that of a regular implementation.    -   Design of the non-Flashing areas of the Authentication Chip are        slightly more complex than to do the same with a with a regular        CMOS design. In particular, standard cell components cannot be        used, making these areas full custom. This is not a problem for        something as small as an Authentication Chip, particularly when        the entire chip does not have to be protected in this manner.

Connections in Polysilicon Layers where Possible

Wherever possible, the connections along which the key or secret dataflows, should be made in the polysilicon layers. Where necessary, theycan be in metal 1, but must never be in the top metal layer (containingthe Tamper Detection Lines).

OverUnderPower Detection Unit

Each Authentication Chip requires an OverUnderPower Detection Unit toprevent Power Supply Attacks. An OverUnderPower Detection Unit detectspower glitches and tests the power level against a Voltage Reference toensure it is within a certain tolerance. The Unit contains a singleVoltage Reference and two comparators. The OverUnderPower Detection Unitwould be connected into the RESET Tamper Detection Line, thus causing aRESET when triggered. A side effect of the OverUnderPower Detection Unitis that as the voltage drops during a power-down, a RESET is triggered,thus erasing any work registers.

No Test Circuitry

Test hardware on an Authentication Chip could very easily introducevulnerabilities. As a result, the Authentication Chip should not containany BIST or scan paths. The Authentication Chip must therefore betestable with external test vectors. This should be possible since theAuthentication Chip is not complex.

Reading ROM

This attack depends on the key being stored in an addressable ROM. Sinceeach Authentication Chip stores its authentication keys in internalFlash memory and not in an addressable ROM, this attack is irrelevant.

Reverse Engineering the Chip

Reverse engineering a chip is only useful when the security ofauthentication lies in the algorithm alone. However our AuthenticationChips rely on a secret key, and not in the secrecy of the algorithm. Ourauthentication algorithm is, by contrast, public, and in any case, anattacker of a high volume consumable is assumed to have been able toobtain detailed plans of the internals of the chip. In light of thesefactors, reverse engineering the chip itself, as opposed to the storeddata, poses no threat.

Usurping the Authentication Process

There are several forms this attack can take, each with varying degreesof success. In all cases, it is assumed that a clone manufacturer willhave access to both the System and the consumable designs. An attackermay attempt to build a chip that tricks the System into returning avalid code instead of generating an authentication code. This attack isnot possible for two reasons. The first reason is that SystemAuthentication chips and Consumable Authentication Chips, althoughphysically identical, are programmed differently. In particular, the RDopcode and the RND opcode are the same, as are the WR and TST opcodes. ASystem authentication Chip cannot perform a RD command since every callis interpreted as a call to RND instead. The second reason this attackwould fail is that separate serial data lines are provided from theSystem to the System and Consumable Authentication Chips. Consequentlyneither chip can see what is being transmitted to or received from theother. If the attacker builds a clone chip that ignores WR commands(which decrement the consumable remaining), Protocol 3 ensures that thesubsequent RD will detect that the WR did not occur. The System willtherefore not go ahead with the use of the consumable, thus thwartingthe attacker. The same is true if an attacker simulates loss of contactbefore authentication—since the authentication does not take place, theuse of the consumable doesn't occur. An attacker is therefore limited tomodifying each System in order for clone consumables to be accepted

Modification of System

The simplest method of modification is to replace the System'sAuthentication Chip with one that simply reports success for each callto TST. This can be thwarted by System calling TST several times foreach authentication, with the first few times providing false values,and expecting a fail from TST. The final call to TST would be expectedto succeed. The number of false calls to TST could be determined by somepart of the returned result from RD or from the system clock.Unfortunately an attacker could simply rewire System so that the newSystem clone authentication chip 53 can monitor the returned result fromthe consumable chip or clock. The clone System Authentication Chip wouldonly return success when that monitored value is presented to its TSTfunction. Clone consumables could then return any value as the hashresult for RD, as the clone System chip would declare that value valid.There is therefore no point for the System to call the SystemAuthentication Chip multiple times, since a rewiring attack will onlywork for the System that has been rewired, and not for all Systems. Asimilar form of attack on a System is a replacement of the System ROM.The ROM program code can be altered so that the Authentication neveroccurs. There is nothing that can be done about this, since the Systemremains in the hands of a consumer. Of course this would void anywarranty, but the consumer may consider the alteration worthwhile if theclone consumable were extremely cheap and more readily available thanthe original item. The System/consumable manufacturer must thereforedetermine how likely an attack of this nature is. Such a study mustinclude given the pricing structure of Systems and Consumables,frequency of System service, advantage to the consumer of having aphysical modification performed, and where consumers would go to get themodification performed. The limit case of modifying a system is for aclone manufacturer to provide a completely clone System which takesclone consumables. This may be simple competition or violation ofpatents. Either way, it is beyond the scope of the Authentication Chipand depends on the technology or service being cloned.

Direct Viewing of Chip Operation by Conventional Probing

In order to view the chip operation, the chip must be operating.However, the Tamper Prevention and Detection circuitry covers thosesections of the chip that process or hold the key. It is not possible toview those sections through the Tamper Prevention lines. An attackercannot simply slice the chip past the Tamper Prevention layer, for thiswill break the Tamper Detection Lines and cause an erasure of all keysat power-up. Simply destroying the erasure circuitry is not sufficient,since the multiple ChipOK bits (now all 0) feeding into multiple unitswithin the Authentication Chip will cause the chip's regular operatingcircuitry to stop functioning. To set up the chip for an attack, then,requires the attacker to delete the Tamper Detection lines, stop theErasure of Flash memory, and somehow rewire the components that reliedon the ChipOK lines. Even if all this could be done, the act of slicingthe chip to this level will most likely destroy the charge patterns inthe non-volatile memory that holds the keys, making the processfruitless.

Direct Viewing of the Non-Volatile Memory

If the Authentication Chip were sliced so that the floating gates of theFlash memory were exposed, without discharging them, then the keys couldprobably be viewed directly using an STM or SKM. However, slicing thechip to this level without discharging the gates is probably impossible.Using wet etching, plasma etching, ion milling, or chemical mechanicalpolishing will almost certainly discharge the small charges present onthe floating gates. This is true of regular Flash memory, but even moreso of multi-level Flash memory.

Viewing the Light Bursts Caused by State Changes

All sections of circuitry that manipulate secret key information areimplemented in the non-Flashing CMOS described above. This prevents theemission of the majority of light bursts. Regular CMOS inverters placedin close proximity to the non-Flashing CMOS will hide any faintemissions caused by capacitor charge and discharge. The inverters areconnected to the Tamper Detection circuitry, so they change state manytimes (at the high clock rate) for each non-Flashing CMOS state change.

Monitoring EMI

The Noise Generator described above will cause circuit noise. The noisewill interfere with other electromagnetic emissions from the chip'sregular activities and thus obscure any meaningful reading of internaldata transfers.

Viewing I_(dd) Fluctuations

The solution against this kind of attack is to decrease the SNR in theI_(dd) signal. This is accomplished by increasing the amount of circuitnoise and decreasing the amount of signal. The Noise Generator circuit(which also acts as a defense against EMI attacks) will also causeenough state changes each cycle to obscure any meaningful information inthe I_(dd) signal. In addition, the special Non-Flashing

CMOS implementation of the key-carrying data paths of the chip preventscurrent from flowing when state changes occur. This has the benefit ofreducing the amount of signal.

Differential Fault Analysis

Differential fault bit errors are introduced in a non-targeted fashionby ionization, microwave radiation, and environmental stress. The mostlikely effect of an attack of this nature is a change in Flash memory(causing an invalid state) or RAM (bad parity). Invalid states and badparity are detected by the Tamper Detection Circuitry, and cause anerasure of the key. Since the Tamper Detection Lines cover the keymanipulation circuitry, any error introduced in the key manipulationcircuitry will be mirrored by an error in a Tamper Detection Line. Ifthe Tamper Detection Line is affected, the chip will either continuallyRESET or simply erase the key upon a power-up, rendering the attackfruitless. Rather than relying on a non-targeted attack and hoping that“just the right part of the chip is affected in just the right way”, anattacker is better off trying to introduce a targeted fault (such asoverwrite attacks, gate destruction etc). For information on thesetargeted fault attacks, see the relevant sections below.

Clock Glitch Attacks

The Clock Filter (described above) eliminates the possibility of clockglitch attacks.

Power Supply Attacks

The OverUnderPower Detection Unit (described above) eliminates thepossibility of power supply attacks.

Overwriting ROM

Authentication Chips store Program code, keys and secret information inFlash memory, and not in ROM. This attack is therefore not possible.

Modifying EEPROM/Flash

Authentication Chips store Program code, keys and secret information inFlash memory. However, Flash memory is covered by two Tamper Preventionand Detection Lines. If either of these lines is broken (in the processof destroying a gate) the attack will be detected on power-up, and thechip will either RESET (continually) or erase the keys from Flashmemory. However, even if the attacker is able to somehow access the bitsof Flash and destroy or short out the gate holding a particular bit,this will force the bit to have no charge or a full charge. These areboth invalid states for the Authentication Chip's usage of themulti-level Flash memory (only the two middle states are valid). Whenthat data value is transferred from Flash, detection circuitry willcause the Erasure Tamper Detection Line to be triggered—thereby erasingthe remainder of Flash memory and RESETing the chip. A ModifyEEPROM/Flash Attack is therefore fruitless.

Gate Destruction Attacks

Gate Destruction Attacks rely on the ability of an attacker to modify asingle gate to cause the chip to reveal information during operation.However any circuitry that manipulates secret information is covered byone of the two Tamper Prevention and Detection lines. If either of theselines is broken (in the process of destroying a gate) the attack will bedetected on power-up, and the chip will either RESET (continually) orerase the keys from Flash memory. To launch this kind of attack, anattacker must first reverse-engineer the chip to determine which gate(s)should be targeted. Once the location of the target gates has beendetermined, the attacker must break the covering Tamper Detection line,stop the Erasure of Flash memory, and somehow rewire the components thatrely on the ChipOK lines. Rewiring the circuitry cannot be done withoutslicing the chip, and even if it could be done, the act of slicing thechip to this level will most likely destroy the charge patterns in thenon-volatile memory that holds the keys, making the process fruitless.

Overwrite Attacks

An Overwrite Attack relies on being able to set individual bits of thekey without knowing the previous value. It relies on probing the chip,as in the Conventional Probing Attack and destroying gates as in theGate Destruction Attack. Both of these attacks (as explained in theirrespective sections), will not succeed due to the use of the TamperPrevention and Detection Circuitry and ChipOK lines. However, even ifthe attacker is able to somehow access the bits of Flash and destroy orshort out the gate holding a particular bit, this will force the bit tohave no charge or a full charge. These are both invalid states for theAuthentication Chip's usage of the multi-level Flash memory (only thetwo middle states are valid). When that data value is transferred fromFlash detection circuitry will cause the Erasure Tamper Detection Lineto be triggered—thereby erasing the remainder of Flash memory andRESETing the chip. In the same way, a parity check on tampered valuesread from RAM will cause the Erasure Tamper Detection Line to betriggered. An Overwrite Attack is therefore fruitless.

Memory Remanence Attack

Any working registers or RAM within the Authentication Chip may beholding part of the authentication keys when power is removed. Theworking registers and RAM would continue to hold the information forsome time after the removal of power. If the chip were sliced so thatthe gates of the registers/RAM were exposed, without discharging them,then the data could probably be viewed directly using an STM. The firstdefense can be found above, in the description of defense against PowerGlitch Attacks. When power is removed, all registers and RAM arecleared, just as the RESET condition causes a clearing of memory. Thechances then, are less for this attack to succeed than for a reading ofthe Flash memory. RAM charges (by nature) are more easily lost thanFlash memory. The slicing of the chip to reveal the RAM will certainlycause the charges to be lost (if they haven't been lost simply due tothe memory not being refreshed and the time taken to perform theslicing). This attack is therefore fruitless.

Chip Theft Attack

There are distinct phases in the lifetime of an Authentication Chip.Chips can be stolen when at any of these stages:

-   -   After manufacture, but before programming of key    -   After programming of key, but before programming of state data    -   After programming of state data, but before insertion into the        consumable or system    -   After insertion into the system or consumable

A theft in between the chip manufacturer and programming station wouldonly provide the clone manufacturer with blank chips. This merelycompromises the sale of Authentication chips, not anything authenticatedby the Authentication chips. Since the programming station is the onlymechanism with consumable and system product keys, a clone manufacturerwould not be able to program the chips with the correct key. Clonemanufacturers would be able to program the blank chips for their ownSystems and Consumables, but it would be difficult to place these itemson the market without detection. The second form of theft can onlyhappen in a situation where an Authentication Chip passes through two ormore distinct programming phases. This is possible, but unlikely. In anycase, the worst situation is where no state data has been programmed, soall of M is read/write. If this were the case, an attacker could attemptto launch an Adaptive Chosen Text Attack on the chip. The HMAC-SHA1algorithm is resistant to such attacks. The third form of theft wouldhave to take place in between the programming station and theinstallation factory. The Authentication chips would already beprogrammed for use in a particular system or for use in a particularconsumable. The only use these chips have to a thief is to place theminto a clone System or clone Consumable. Clone systems are irrelevant—acloned System would not even require an authentication chip 53. Forclone Consumables, such a theft would limit the number of clonedproducts to the number of chips stolen. A single theft should not createa supply constant enough to provide clone manufacturers with acost-effective business. The final form of theft is where the System orConsumable itself is stolen. When the theft occurs at the manufacturer,physical security protocols must be enhanced. If the theft occursanywhere else, it is a matter of concern only for the owner of the itemand the police or insurance company. The security mechanisms that theAuthentication Chip uses assume that the consumables and systems are inthe hands of the public. Consequently, having them stolen makes nodifference to the security of the keys.

Authentication Chip Design

The Authentication Chip has a physical and a logical external interface.The physical interface defines how the Authentication Chip can beconnected to a physical System, and the logical interface determines howthat System can communicate with the Authentication Chip.

Physical Interface

The Authentication Chip is a small 4-pin CMOS package (actual internalsize is approximately 0.30 mm² using 0.25 μm Flash process). The 4 pinsare GND, CLK, Power, and Data. Power is a nominal voltage. If thevoltage deviates from this by more than a fixed amount, the chip willRESET. The recommended clock speed is 4-10 MHz. Internal circuitryfilters the clock signal to ensure that a safe maximum clock speed isnot exceeded. Data is transmitted and received one bit at a time alongthe serial data line. The chip performs a RESET upon power-up,power-down. In addition, tamper detection and prevention circuitry inthe chip will cause the chip to either RESET or erase Flash memory(depending on the attack detected) if an attack is detected. A specialProgramming Mode is enabled by holding the CLK voltage at a particularlevel. This is defined further in the next section.

Logical Interface

The Authentication Chip has two operating modes—a Normal Mode and aProgramming Mode. The two modes are required because the operatingprogram code is stored in Flash memory instead of ROM (for securityreasons). The Programming mode is used for testing purposes aftermanufacture and to load up the operating program code, while the normalmode is used for all subsequent usage of the chip.

Programming Mode

The Programming Mode is enabled by holding a specific voltage on the CLKline for a given amount of time. When the chip enters Programming Mode,all Flash memory is erased (including all secret key information and anyprogram code). The Authentication Chip then validates the erasure. Ifthe erasure was successful, the Authentication Chip receives 384 bytesof data corresponding to the new program code. The bytes are transferredin order byte₀ to byte₃₈₃. The bits are transferred from bit₀ to bit₇.Once all 384 bytes of program code have been loaded, the AuthenticationChip hangs. If the erasure was not successful, the Authentication Chipwill hang without loading any data into the Flash memory. After the chiphas been programmed, it can be restarted. When the chip is RESET with anormal voltage on the CLK line, Normal Mode is entered.

Normal Mode

Whenever the Authentication Chip is not in Programming Mode, it is inNormal Mode. When the Authentication Chip starts up in Normal Mode (forexample a power-up RESET), it executes the program currently stored inthe program code region of Flash memory. The program code implements acommunication mechanism between the System and Authentication Chip,accepting commands and data from the System and producing output values.Since the Authentication Chip communicates serially, bits aretransferred one at a time. The System communicates with theAuthentication Chips via a simple operation command set. Each command isdefined by 3-bit opcode. The interpretation of the opcode depends on thecurrent value of the IsTrusted bit and the IsWritten bit.

The following operations are defined:

Op T W Mn Input Output Description 000 — — CLR — — Clear 001 0 0 SSI[160, 160, 160] — Set Secret Information 010 0 1 RD [160, 160] [256,160] Read M securely 010 1 1 RND — [160, 160] Random 011 0 1 WR [256] —Write M 011 1 1 TST [256, 160] [1] Test 100 0 1 SAM [32] [32] Set AccessMode 101 — 1 GIT — [1] Get Is Trusted 110 — 1 SMT [32] — Set MinTicks Op= Opcode, T = IsTrusted value, W = IsWritten value, Mn = Mnemonic, [n] =number of bits required for parameter

Any command not defined in this table is interpreted as NOP (Nooperation). Examples include opcodes 110 and 111 (regardless ofIsTrusted or IsWritten values), and any opcode other than SSI whenIsWritten=0. Note that the opcodes for RD and RND are the same, as arethe opcodes for WR and TST. The actual command run upon receipt of theopcode will depend on the current value of the IsTrusted bit (as long asIsWritten is 1). Where the IsTrusted bit is clear, RD and WR functionswill be called. Where the IsTrusted bit is set, RND and TST functionswill be called. The two sets of commands are mutually exclusive betweentrusted and non-trusted Authentication Chips. In order to execute acommand on an Authentication Chip, a client (such as System) sends thecommand opcode followed by the required input parameters for thatopcode. The opcode is sent least significant bit through to mostsignificant bit. For example, to send the SSI command, the bits 1, 0,and 0 would be sent in that order. Each input parameter is sent in thesame way, least significant bit first through to most significant bitlast. Return values are read in the same way—least significant bit firstand most significant bit last. The client must know how many bits toretrieve.

In some cases, the output bits from one chip's command can be feddirectly as the input bits to another chip's command. An example of thisis the RND and RD commands. The output bits from a call to RND on atrusted Authentication Chip do not have to be kept by System. Instead,System can transfer the output bits directly to the input of thenon-trusted Authentication Chip's RD command. The description of eachcommand points out where this is so. Each of the commands is examined indetail in the subsequent sections. Note that some algorithms arespecifically designed because the permanent registers are kept in Flashmemory.

Registers

The memory within the Authentication Chip contains some non-volatilememory to store the variables required by the Authentication Protocol.The following non-volatile (Flash) variables are defined:

Size Variable Name (in bits) Description M[0 . . . 15] 256 16 words(each 16 bits) containing state data such as serial numbers, mediaremaining etc. K₁ 160 Key used to transform R during authentication. K₂160 Key used to transform M during authentication. R 160 Current randomnumber AccessMode[0 . . . 15] 32 The 16 sets of 2-bit AccessMode valuesfor M[n]. MinTicks 32 The minimum number of clock ticks between calls tokey-based functions SIWritten 1 If set, the secret key information (K₁,K₂, and R) has been written to the chip. If clear, the secretinformation has not been written yet. IsTrusted 1 If set, the RND andTST functions can be called, but RD and WR functions cannot be called.If clear, the RND and TST functions cannot be called, but RD and WRfunctions can be called. Total bits 802

Architecture Overview

This section chapter provides the high-level definition of apurpose-built CPU capable of implementing the functionality required ofan Authentication Chip. Note that this CPU is not a general purpose CPU.It is tailor-made for implementing the Authentication logic. Theauthentication commands that a user of an Authentication Chip sees, suchas WRITE, TST, RND etc are all implemented as small programs written inthe CPU instruction set. The CPU contains a 32-bit Accumulator (which isused in most operations), and a number of registers. The CPU operates on8-bit instructions specifically tailored to implementing authenticationlogic. Each 8-bit instruction typically consists of a 4-bit opcode, anda 4-bit operand.

Operating Speed

An internal Clock Frequency Limiter Unit prevents the chip fromoperating at speeds any faster than a predetermined frequency. Thefrequency is built into the chip during manufacture, and cannot bechanged. The frequency is recommended to be about 4-10 MHz.

Composition and Block Diagram

The Authentication Chip contains the following components:

Unit Name CMOS Type Description Clock Normal Ensures the operatingfrequency Frequency of the Authentication Chip Limiter does not exceed aspecific maximum frequency. OverUnderPower Normal Ensures that the powersupply Detection Unit remains in a valid operating range. ProgrammingNormal Allows users to enter Programming Mode Detection Mode. Unit NoiseNormal For generating I_(dd) noise and for Generator use in the TamperPrevention and Detection circuitry. State Normal for controlling the twooperating Machine modes of the chip (Programming Mode and Normal Mode).This includes generating the two operating cycles of the CPU, stallingduring long command operations, and storing the op-code and operandduring operating cycles. I/O Unit Normal Responsible for communicatingserially with the outside world. ALU Non- Contains the 32-bitaccumulator flashing as well as the general math- ematical and logicaloperators. MinTicks Normal Responsible for a programmable Unit (99%),Non- minimum delay (via a countdown) flashing between certain key-based(1%) operations. Address Normal Generates direct, indirect, andGenerator (99%), Non- indexed addresses as required by Unit flashingspecific operands. (1%) Program Normal Includes the 9 bit PC (programCounter Unit counter), as well as logic for branching and subroutinecontrol Memory Unit Non- Addressed by 9 bits of address. flashing Itcontains an 8-bit wide program Flash memory, and 32-bit wide Flashmemory, RAM, and look-up tables. Also contains Programming Modecircuitry to enable loading of program code.

FIG. 181 illustrates a schematic block diagram of the AuthenticationChip. The tamper prevention and Detection Circuitry is not shown: TheNoise Generator, OverUnderPower Detection Unit, and ProgrammingModeDetection Unit are connected to the Tamper Prevention and DetectionCircuitry and not to the remaining units.

Memory Map

FIG. 182 illustrates an example memory map. Although the AuthenticationChip does not have external memory, it does have internal memory. Theinternal memory is addressed by 9 bits, and is either 32-bits wide or8-bits wide (depending on address). The 32-bit wide memory is used tohold the non-volatile data, the variables used for HMAC-SHA1, andconstants. The 8-bit wide memory is used to hold the program and thevarious jump tables used by the program. The address breakup (includingreserved memory ranges) is designed to optimize address generation anddecoding.

Constants

FIG. 183 illustrates an example of the constants memory map. TheConstants region consists of 32-bit constants. These are the simpleconstants (such as 32-bits of all 0 and 32-bits of all 1), the constantsused by the HMAC algorithm, and the constants y₀₋₃ and h₀₋₄ required foruse in the SHA-1 algorithm. None of these values are affected by aRESET. The only opcode that makes use of constants is LDK. In this case,the operands and the memory placement are closely linked, in order tominimize the address generation and decoding.

RAM

FIG. 184 illustrates an example of the RAM memory map. The RAM regionconsists of the 32 parity-checked 32-bit registers required for thegeneral functioning of the Authentication Chip, but only during theoperation of the chip. RAM is volatile memory, which means that oncepower is removed, the values are lost. Note that in actual fact, memoryretains its value for some period of time after power-down (due tomemory remnance), but cannot be considered to be available uponpower-up. This has issues for security that are addressed in othersections of this document. RAM contains the variables used for theHMAC-SHA1 algorithm, namely: A-E, the temporary variable T, space forthe 160-bit working hash value H, space for temporary storage of a hashresult (required by HMAC) B160, and the space for the 512 bits ofexpanded hashing memory X. All RAM values are cleared to 0 upon a RESET,although any program code should not take this for granted.

Opcodes that make use of RAM addresses are LD, ST, ADD, LOG, XOR, andRPL. In all cases, the operands and the memory placement are closelylinked, in order to minimize the address generation and decoding(multiword variables are stored most significant word first).

Flash Memory—Variables

FIG. 185 illustrates an example of the Flash memory variables memorymap. The Flash memory region contains the non-volatile information inthe Authentication Chip. Flash memory retains its value after power isremoved, and can be expected to be unchanged when the power is nextturned on. The non-volatile information kept in multi-state Flash memoryincludes the two 160-bit keys (K₁ and K₂), the current random numbervalue (R), the state data (M), the MinTicks value (MT), the AccessModevalue (AM), and the IsWritten (ISW) and IsTrusted (IST) flags. Flashvalues are unchanged by a RESET, but are cleared (to 0) upon enteringProgramming Mode. Operations that make use of Flash addresses are LD,ST, ADD, RPL, ROR, CLR, and SET. In all cases, the operands and thememory placement are closely linked, in order to minimize the addressgeneration and decoding. Multiword variables K₁, K₂, and M are storedmost significant word first due to addressing requirements. Theaddressing scheme used is a base address offset by an index that startsat N and ends at 0. Thus M_(N) is the first word accessed, and M₀ is thelast 32-bit word accessed in loop processing. Multiword variable R isstored least significant word first for ease of LFSR generation usingthe same indexing scheme.

Flash Memory—Program

FIG. 186 illustrates an example of the Flash memory program memory map.The second multi-state Flash memory region is 384×8-bits. The regioncontains the address tables for the JSR, JSI and TBR instructions, theoffsets for the DBR commands, constants and the program itself. TheFlash memory is unaffected by a RESET, but is cleared (to 0) uponentering Programming Mode. Once Programming Mode has been entered, the8-bit Flash memory can be loaded with a new set of 384 bytes. Once thishas been done, the chip can be RESET and the normal chip operations canoccur.

Registers

A number of registers are defined in the Authentication Chip. They areused for temporary storage during function execution. Some are used forarithmetic functions, others are used for counting and indexing, andothers are used for serial I/O. These registers do not need to be keptin non-volatile (Flash) memory. They can be read or written without theneed for an erase cycle (unlike Flash memory). Temporary storageregisters that contain secret information still need to be protectedfrom physical attack by Tamper Prevention and Detection circuitry andparity checks.

All registers are cleared to 0 on a RESET. However, program code shouldnot assume any particular state, and set up register valuesappropriately. Note that these registers do not include the various OKbits defined for the Tamper Prevention and Detection circuitry. The OKbits are scattered throughout the various units and are set to 1 upon aRESET.

Cycle

The 1-bit Cycle value determines whether the CPU is in a Fetch cycle (0)or an Execute cycle (1). Cycle is actually derived from a 1-bit registerthat holds the previous Cycle value. Cycle is not directly accessiblefrom the instruction set. It is an internal register only.

Program Counter

A 6-level deep 9-bit Program Counter Array (PCA) is defined. It isindexed by a 3-bit Stack Pointer (SP). The current Program Counter (PC),containing the address of the currently executing instruction, iseffectively PCA[SP]. In addition, a 9-bit Adr register is defined,containing the resolved address of the current memory reference (forindexed or indirect memory accesses). The PCA, SP, and Adr registers arenot directly accessible from the instruction set. They are internalregisters only

CMD

The 8-bit CMD register is used to hold the currently executing command.While the CMD register is not directly accessible from the instructionset, and is an internal register only.

Accumulator and Z Flag

The Accumulator is a 32-bit general-purpose register. It is used as oneof the inputs to all arithmetic operations, and is the register used fortransferring information between memory registers. The Z register is a1-bit flag, and is updated each time the Accumulator is written to. TheZ register contains the zero-ness of the Accumulator. Z=1 if the lastvalue written to the Accumulator was 0, and 0 if the last value writtenwas non-0. Both the Accumulator and Z registers are directly accessiblefrom the instruction set.

Counters

A number of special purpose counters/index registers are defined:

Name Register Size Bits Description C1 1 × 3 3 Counter used to indexarrays: AE, B160, M, H, y, and h. C2 1 × 5 5 General purpose counterN₁₋₄ 4 × 4 16 Used to index array X

All these counter registers are directly accessible from the instructionset. Special instructions exist to load them with specific values, andother instructions exist to decrement or increment them, or to branchdepending on the whether or not the specific counter is zero. There arealso 2 special flags (not registers) associated with C1 and C2, andthese flags hold the zero-ness of C1 or C2. The flags are used for loopcontrol, and are listed here, for although they are not registers, theycan be tested like registers.

Name Description C1Z 1 = C1 is current zero, 0 = C1 is currentlynon-zero. C2Z 1 = C2 is current zero, 0 = C2 is currently non-zero.

Flags

A number of 1-bit flags, corresponding to CPU operating modes, aredefined:

Name Bits Description WE 1 WriteEnable for X register array: 0 = Writesto X registers become no-ops 1 = Writes to X registers are carried outK2MX 1 0 = K1 is accessed during K references. Reads from M areinterpreted as reads of 0 1 = K2 is accessed during K references. Readsfrom M succeed.

All these 1-bit flags are directly accessible from the instruction set.Special instructions exist to set and clear these flags. Registers usedfor Write Integrity

Name Bits Description EE 1 Corresponds to the EqEncountered variable inthe WR command pseudocode. Used during the writing of multi- precisiondata values to determine whether all more significant components havebeen equal to their previous values. DE 1 Corresponds to theDecEncountered variable in the WR command pseudocode. Used during thewriting of multi- precision data values to determine whether a moresignificant components has been decremented already.

Registers Used for I/O

Four 1-bit registers are defined for communication between the client(System) and the Authentication Chip. These registers are InBit,InBitValid, OutBit, and OutBitValid. InBit and InBitValid provide themeans for clients to pass commands and data to the Authentication Chip.OutBit and OutBitValid provide the means for clients to get informationfrom the Authentication Chip. A client sends commands and parameter bitsto the Authentication Chip one bit at a time. Since the AuthenticationChip is a slave device, from the Authentication Chip's point of view:

-   -   Reads from InBit will hang while InBitValid is clear. InBitValid        will remain clear until the client in has written the next input        bit to InBit. Reading InBit clears the InBitValid bit to allow        the next InBit to be read from the client. A client cannot write        a bit to the Authentication Chip unless the InBitValid bit is        clear.    -   Writes to OutBit will hang while OutBitValid is set. OutBitValid        will remain set until the client has read the bit from OutBit.        Writing OutBit sets the OutBitValid bit to allow the next OutBit        to be read by the client. A client cannot read a bit from the        Authentication Chip unless the OutBitValid bit is set.

Registers Used for Timing Access

A single 32-bit register is defined for use as a timer. The MTR(MinTicksRemaining) register decrements every time an instruction isexecuted. Once the MTR register gets to 0, it stays at zero. Associatedwith MTR is a 1-bit flag MTRZ, which contains the zero-ness of the MTRregister. If MTRZ is 1, then the MTR register is zero. If MTRZ is 0,then the MTR register is not zero yet. MTR always starts off at theMinTicks value (after a RESET or a specific key-accessing function), andeventually decrements to 0. While MTR can be set and MTRZ tested byspecific instructions, the value of MTR cannot be directly read by anyinstruction.

Register Summary

The following table summarizes all temporary registers (ordered byregister name). It lists register names, size (in bits), as well aswhere the specified register can be found.

Register Name Bits Parity Where Found Acc 32 1 Arithmetic Logic Unit Adr9 1 Address Generator Unit AMT 32 Arithmetic Logic Unit C1 3 1 AddressGenerator Unit C2 5 1 Address Generator Unit CMD 8 1 State Machine Cycle(Old = prev 1 State Machine Cycle DE 1 Arithmetic Logic Unit EE 1Arithmetic Logic Unit InBit 1 Input Output Unit InBitValid 1 InputOutput Unit K2MX 1 Address Generator Unit MTR 32 1 MinTicks Unit MTRZ 1MinTicks Unit N[1-4] 16 4 Address Generator Unit OutBit 1 Input OutputUnit OutBitValid 1 Input Output Unit PCA 54 6 Program Counter Unit RTMP1 Arithmetic Logic Unit SP 3 1 Program Counter Unit WE 1 Memory Unit Z 1Arithmetic Logic Unit Total bits 206 17

Instruction Set

The CPU operates on 8-bit instructions specifically tailored toimplementing authentication logic. The majority of 8-bit instructionconsists of a 4-bit opcode, and a 4-bit operand. The high-order 4 bitscontains the opcode, and the low-order 4 bits contains the operand.

Opcodes and Operands (Summary)

The opcodes are summarized in the following table:

Opcode Mnemonic Simple Description 0000 TBR Test and branch. 0001 DBRDecrement and branch 001 JSR Jump subroutine via table 01000 RTS Returnfrom subroutine 01001 JSI Jump subroutine indirect 0101 SC Set counter0110 CLR Clear specific flash registers 0111 SET Set bits in specificflash register 1000 ADD Add a 32 bit value to the Accumulator 1001 LOGLogical operation (AND, and OR) 1010 XOR Exclusive-OR Accumulator withsome value 1011 LD Load Accumulator from specified location 1100 RORRotate Accumulator right 1101 RPL Replace bits 1110 LDK Load Accumulatorwith a constant 1111 ST Store Accumulator in specified location

The following table is a summary of which operands can be used withwhich opcodes. The table is ordered alphabetically by opcode mnemonic.The binary value for each operand can be found in the subsequent tables.

Opcode Valid Operand ADD {A, B, C, D, E, T, MT, AM, AE[C1], B160[C1],H[C1], M[C1], K[C1], R[C1], X[N4]} CLR {WE, K2MX, M[C1], Group1, Group2}DBR {C1, C2}, Offset into DBR Table JSI { } JSR Offset into Table 1 LD{A, B, C, D, E, T, MT, AM, AE[C1], B160[C1], H[C1], M[C1], K[C1], R[C1],X[N4]} LDK {0x0000 . . . , 0x3636 . . . , 0x5C5C . . . , 0xFFFF, h[C1],y[C1]} LOG {AND, OR}, {A, B, C, D, E, T, MT, AM} ROR {InBit, OutBit,LFSR, RLFSR, IST, ISW, MTRZ, 1, 2, 27, 31} RPL {Init, MHI, MLO} RTS { }SC {C1, C2}, Offset into counter list SET {WE, K2MX, Nx, MTR, IST, ISW}ST {A, B, C, D, E, T, MT, AM, AE[C1], B160[C1], H[C1], M[C1], K[C1],R[C1], X[N4]} TBR {0, 1}, Offset into Table 1 XOR {A, B, C, D, E, T, MT,AM, X[N1], X[N2], X[N3], X[N4]}

The following operand table shows the interpretation of the 4-bitoperands where all 4 bits are used for direct interpretation.

Operand ADD, LD, ST XOR ROR LDK RPL SET CLR 0000 E E InBit 0x00 . . .Init WE WE 0001 D D OutBit 0x36 . . . — K2MX K2MX 0010 C C RB 0x5C . . .— Nx — 0011 B B XRB 0xFF . . . — — — 0100 A A IST y[C1] — IST — 0101 T TISW — — ISW — 0110 MT MT MTRZ — — MTR — 0111 AM AM 1 — — — — 1000 AE[C1]— — h[C1] — — — 1001 B160[C1] — 2 — — — — 1010 H[C1] — 27 — — — — 1011 —— — — — — — 1100 R[C1] X[N1] 31 — — — R 1101 K[C1] X[N2] — — — — Group11110 M[C1] X[N3] — — MLO — M[C1] 1111 X[N4] X[N4] — — MHI — Group2

The following instructions make a selection based upon the highest bitof the operand:

Which Which Which Counter? operation? Value? Operand₃ (DBR, SC) (LOG)(TBR) 0 C1 AND Zero 1 C2 OR Non-zero

The lowest 3 bits of the operand are either offsets (DBR, TBR), valuesfrom a special table (SC) or as in the case of LOG, they select thesecond input for the logical operation. The interpretation matches theinterpretation for the ADD, LD, and ST opcodes:

Operand²⁻⁰ LOG Input2 SC Value 000 E 2 001 D 3 010 C 4 011 B 7 100 A 10101 T 15 110 MT 19 111 AM 31

ADD—Add To Accumulator

Mnemonic: ADD Opcode: 1000 Usage: ADD Value

The ADD instruction adds the specified operand to the Accumulator viamodulo 2³² addition. The operand is one of A, B, C, D, E, T, AM, MT,AE[C1], H[C1], B160[C1], R[C1], K[C1], M[C1], or X[N4]. The Z flag isalso set during this operation, depending on whether the value loaded iszero or not.

CLR—Clear Bits

Mnemonic: CLR Opcode: 0110 Usage: CLR Flag/Register

The CLR instruction causes the specified internal flag or Flash memoryregisters to be cleared. In the case of Flash memory, although the CLRinstruction takes some time the next instruction is stalled until theerasure of Flash memory has finished. The registers that can be clearedare WE and K2MX. The Flash memory that can be cleared are: R, M[C1],Group1, and Group2. Group1 is the IST and ISW flags. If these arecleared, then the only valid high level command is the SSI instruction.Group2 is the MT, AM, K1 and K2 registers. R is erased separately sinceit must be updated after each call to TST. M is also erased via an indexmechanism to allow individual parts of M to be updated. There is also acorresponding SET instruction.

DBR—Decrement and Branch

Mnemonic: DBR Opcode: 0001 Usage: DBR Counter, Offset

This instruction provides the mechanism for building simple loops. Thehigh hit of the operand selects between testing C1 or C2 (the twocounters). If the specified counter is non-zero, then the counter isdecremented and the value at the given offset (sign extended) is addedto the PC. If the specified counter is zero, it is decremented andprocessing continues at PC+1. The 8-entry offset table is stored ataddress 0 1100 0000 (the 64^(th) entry of the program memory). The 8bits of offset are treated as a signed number. Thus 0xFF is treated as−1, and 0x01 is treated as +1. Typically the value will be negative foruse in loops.

JSI—Jump Subroutine Indirect

Mnemonic: JSI Opcode: 01001 Usage: JSI (Acc)

The JSI instruction allows the jumping to a subroutine dependant on thevalue currently in the Accumulator. The instruction pushes the currentPC onto the stack, and loads the PC with a new value. The upper 8 bitsof the new PC are loaded from Jump Table 2 (offset given by the lower 5bits of the Accumulator), and the lowest bit of the PC is cleared to 0.Thus all subroutines must start at even addresses. The stack providesfor 6 levels of execution (5 subroutines deep). It is the responsibilityof the programmer to ensure that this depth is not exceeded or thereturn value will be overwritten (since the stack wraps).

JSR—Jump Subroutine

Mnemonic: JSR Opcode: 001 Usage: JSR Offset

The JSR instruction provides for the most common usage of the subroutineconstruct. The instruction pushes the current PC onto the stack, andloads the PC with a new value. The upper 8 bits of the new PC valuecomes from Address Table 1, with the offset into the table provided bythe 5-bit operand (32 possible addresses). The lowest bit of the new PCis cleared to 0. Thus all subroutines must start at even addresses. Thestack provides for 6 levels of execution (5 subroutines deep). It is theresponsibility of the programmer to ensure that this depth is notexceeded or the return value will be overwritten (since the stackwraps).

LD—Load Accumulator

Mnemonic: LD Opcode: 1011 Usage: LD Value

The LD instruction loads the Accumulator from the specified operand. Theoperand is one of A, B, C, D, E, T, AM, MT, AE[C1], H[C1], B160[C1],R[C1], K[C1], M[C1], or X[N4]. The Z flag is also set during thisoperation, depending on whether the value loaded is zero or not.

LDK—Load Constant

Mnemonic: LDK Opcode: 1110 Usage: LDK Constant

The LDK instruction loads the Accumulator with the specified constant.The constants are those 32-bit values required for HMAC-SHA™ and all 0sand all 1s as most useful for general purpose processing. Consequentlythey are a choice of:

0x00000000

0x36363636

0x5C5C5C5C

0xFFFFFFFF

or from the h and y constant tables, indexed by Cl. The h and y constanttables hold the 32-bit tabular constants required for HMAC-SHA1. The Zflag is also set during this operation, depending on whether theconstant loaded is zero or not.

LOG—Logical Operation

Mnemonic: LOG Opcode: 1001 Usage: LOG Operation Value

The LOG instruction performs 32-bit bitwise logical operations on theAccumulator and a specified value. The two operations supported by theLOG instruction are AND and OR. Bitwise NOT and XOR operations aresupported by the XOR instruction. The 32-bit value to be ANDed or ORedwith the accumulator is one of the following: A, B, C, D, E, T, MT andAM. The Z flag is also set during this operation, depending on whetherresultant 32-bit value (loaded into the Accumulator) is zero or not.

ROR—Rotate Right

Mnemonic: ROR Opcode: 1100 Usage: ROR Value

The ROR instruction provides a way of rotating the Accumulator right aset number of bits. The bit coming in at the top of the Accumulator (tobecome bit 31) can either come from the previous bit 0 of theAccumulator, or from an external 1-bit flag (such as a flag, or theserial input connection). The bit rotated out can also be output fromthe serial connection, or combined with an external flag.

The allowed operands are: InBit, OutBit, LFSR, RLFSR, IST, ISW, MTRZ, 1,2, 27, and 31. The Z flag is also set during this operation, dependingon whether resultant 32-bit value (loaded into the Accumulator) is zeroor not. In its simplest form, the operand for the ROR instruction is oneof 1, 2, 27, 31, indicating how many bit positions the Accumulatorshould be rotated. For these operands, there is no external input oroutput—the bits of the Accumulator are merely rotated right. Withoperands IST, ISW, and MTRZ, the appropriate flag is transferred to thehighest bit of the Accumulator. The remainder of the Accumulator isshifted right one bit position (bit 31 becomes bit 30 etc), with lowestbit of the Accumulator shifted out. With operand InBit, the next serialinput bit is transferred to the highest bit of the Accumulator. TheInBitValid bit is then cleared. If there is no input bit available fromthe client yet, execution is suspended until there is one. The remainderof the Accumulator is shifted right one bit position (bit 31 becomes bit30 etc), with lowest bit of the Accumulator shifted out.

With operand OutBit, the Accumulator is shifted right one bit position.The bit shifted out from bit 0 is stored in the OutBit flag and theOutBitValid flag is set. It is therefore ready for a client to read. Ifthe OutBitValid flag is already set, execution of the instruction stallsuntil the OutBit bit has been read by the client (and the OutBitValidflag cleared). The new bit shifted in to bit 31 should be consideredgarbage (actually the value currently in the InBit register). Finally,the RB and XRB operands allow the implementation of LFSRs and multipleprecision shift registers. With RB, the bit shifted out (formally bit 0)is written to the RTMP register. The register currently in the RTMPregister becomes the new bit 31 of the Accumulator. Performing multipleROR RB commands over several 32-bit values implements a multipleprecision rotate/shift right. The XRB operates in the same way as RB, inthat the current value in the RTMP register becomes the new bit 31 ofthe Accumulator. However with the XRB instruction, the bit formallyknown as bit 0 does not simply replace RTMP (as in the RB instruction).Instead, it is XORed with RTMP, and the result stored in RTMP. Thisallows the implementation of long LFSRs, as required by theAuthentication protocol.

RPL—Replace Bits

Mnemonic: RPL Opcode: 1101 Usage: ROR Value

The RPL instruction is designed for implementing the high level WRITEcommand in the Authentication Chip. The instruction is designed toreplace the upper 16 bits of the Accumulator by the value that willeventually be written to the M array (dependant on the Access Modevalue). The instruction takes 3 operands: Init, MHI, and MLO. The Initoperand sets all internal flags and prepares the RPL unit within the ALUfor subsequent processing. The Accumulator is transferred to an internalAccessMode register. The Accumulator should have been loaded from the AMFlash memory location before the call to RPL Init in the case ofimplementing the WRITE command, or with 0 in the case of implementingthe TST command. The Accumulator is left unchanged. The MHI and MLOoperands refer to whether the upper or lower 16 bits of M[Cl] will beused in the comparison against the (always) upper 16 bits of theAccumulator. Each MHI and MLO instruction executed uses the subsequent 2bits from the initialized AccessMode value. The first execution of MHIor MLO uses the lowest 2 bits, the next uses the second two bits etc.

RTS—Return from Subroutine

Mnemonic: RTS Opcode: 01000 Usage: RTS

The RTS instruction causes execution to resume at the instruction afterthe most recently executed JSR or JSI instruction. Hence the term:returning from the subroutine. In actuality, the instruction pulls thesaved PC from the stack, adds 1, and resumes execution at the resultantaddress. Although 6 levels of execution are provided for (5subroutines), it is the responsibility of the programmer to balance eachJSR and JSI instruction with an RTS. An RTS executed with no previousJSR will cause execution to begin at whatever address happens to bepulled from the stack.

SC—Set Counter

Mnemonic: SC Opcode: 0101 Usage: SC Counter Value

The SC instruction is used to load a counter with a particular value.The operand determines which of counters C1 and C2 is to be loaded. TheValue to be loaded is one of 2, 3, 4, 7, 10, 15, 19, and 31. The countervalues are used for looping and indexing. Both C1 and C2 can be used forlooping constructs (when combined with the DBR instruction), while onlyCl can be used for indexing 32-bit parts of multi-precision variables.

SET—Set Bits

Mnemonic: SET Opcode: 0111 Usage: SET Flag/Register

The SET instruction allows the setting of particular flags or flashmemory. There is also a corresponding CLR instruction. The WE and K2MXoperands each set the specified flag for later processing. The IST andISW operands each set the appropriate bit in Flash memory, while the MTRoperand transfers the current value in the Accumulator into the MTRregister. The SET Nx command loads N1-N4 with the following constants:

Constant Initial X[N] Index Loaded referred to N1 2 X[13] N2 7 X[8] N313 X[2] N4 15 X[0]

Note that each initial X[N_(n)] referred to matches the optimized SHA-1algorithm initial states for indexes N1-N4. When each index value N_(n)decrements, the effective X[N] increments. This is because the X wordsare stored in memory with most significant word first.

ST—Store Accumulator

Mnemonic: ST Opcode: 1111 Usage: ST Location

The ST instruction is stores the current value of the Accumulator in thespecified location. The location is one of A, B, C, D, E, T, AM, MT,AE[C1], H[C1], B160[C1], R[C1], K[C1], M[C1], or X[N4]. The X[N4]operand has the side effect of advancing the N4 index. After the storehas taken place, N4 will be pointing to the next element in the X array.N4 decrements by 1, but since the X array is ordered from high to low,to decrement the index advances to the next element in the array. If thedestination is in Flash memory, the effect of the ST instruction is toset the bits in the Flash memory corresponding to the bits in theAccumulator. To ensure a store of the exact value from the Accumulator,be sure to use the CLR instruction to erase the appropriate memorylocation first.

TBR—Test and Branch

Mnemonic: TBR Opcode: 0000 Usage: TBR Value Index

The Test and Branch instruction tests whether the Accumulator is zero ornon-zero, and then branches to the given address if the Accumulator'scurrent state matches that being tested for. If the Z flag matches theTRB test, replace the PC by 9 bit value where bit0=0 and upper 8 bitscome from MU. Otherwise increment current PC by 1. The Value operand iseither 0 or 1. A 0 indicates the test is for the Accumulator to be zero.A 1 indicates the test is for the Accumulator to be non-zero. The Indexoperand indicates where execution is to jump to should the test succeed.The remaining 3 bits of operand index into the lowest 8 entries of JumpTable 1. The upper 8 bits are taken from the table, and the lowest bit(bit 0) is cleared to 0. CMD is cleared to 0 upon a RESET. 0 istranslated as TBR 0, which means branch to the address stored in addressoffset 0 if the Accumulator=0. Since the Accumulator and Z flag are alsocleared to 0 on a RESET, the test will be true, so the net effect is ajump to the address stored in the 0th entry in the jump table.

XOR—Exclusive OR

Mnemonic: XOR Opcode: 1010 Usage: XOR Value

The XOR instruction performs a 32-bit bitwise XOR with the Accumulator,and stores the result in the Accumulator. The operand is one of A, B, C,D, E, T, AM, MT, X[N1], X[N2], X[N3], or X[N4]. The Z flag is also setduring this operation, depending on the result (i.e. what value isloaded into the Accumulator). A bitwise NOT operation can be performedby XORing the Accumulator with 0xFFFFFFFF (via the LDK instruction). TheX[N] operands have a side effect of advancing the appropriate index tothe next value (after the operation). After the XOR has taken place, theindex will be pointing to the next element in the X array. N4 is alsoadvanced by the ST X[N4] instruction. The index decrements by 1, butsince the X array is ordered from high to low, to decrement the indexadvances to the next element in the array.

ProgrammingMode Detection Unit

The ProgrammingMode Detection Unit monitors the input clock voltage. Ifthe clock voltage is a particular value the Erase Tamper Detection Lineis triggered to erase all keys, program code, secret information etc andenter Program Mode. The ProgrammingMode Detection Unit can beimplemented with regular CMOS, since the key does not pass through thisunit. It does not have to be implemented with non-flashing CMOS. Thereis no particular need to cover the ProgrammingMode Detection Unit by theTamper Detection Lines, since an attacker can always place the chip inProgrammingMode via the CLK input. The use of the Erase Tamper DetectionLine as the signal for entering Programming Mode means that if anattacker wants to use Programming Mode as part of an attack, the EraseTamper Detection Lines must be active and functional. This makes anattack on the Authentication Chip far more difficult.

Noise Generator

The Noise Generator can be implemented with regular CMOS, since the keydoes not pass through this unit. It does not have to be implemented withnon-flashing CMOS. However, the Noise Generator must be protected byboth Tamper Detection and Prevention lines so that if an attackerattempts to tamper with the unit, the chip will either RESET or eraseall secret information. In addition, the bits in the LFSR must bevalidated to ensure they have not been tampered with (i.e. a paritycheck). If the parity check fails, the Erase Tamper Detection Line istriggered. Finally, all 64 bits of the Noise Generator are ORed into asingle bit. If this bit is 0, the Erase Tamper Detection Line istriggered. This is because 0 is an invalid state for an LFSR. There isno point in using an OK bit setup since the Noise Generator bits areonly used by the Tamper Detection and Prevention circuitry.

State Machine

The State Machine is responsible for generating the two operating cyclesof the CPU, stalling during long command operations, and storing theop-code and operand during operating cycles. The State Machine can beimplemented with regular CMOS, since the key does not pass through thisunit. It does not have to be implemented with non-flashing CMOS.However, the opcode/operand latch needs to be parity-checked. The logicand registers contained in the State Machine must be covered by bothTamper Detection Lines. This is to ensure that the instructions to beexecuted are not changed by an attacker.

The Authentication Chip does not require the high speeds and throughputof a general purpose CPU. It must operate fast enough to perform theauthentication protocols, but not faster. Rather than have specializedcircuitry for optimizing branch control or executing opcodes whilefetching the next one (and all the complexity associated with that), thestate machine adopts a simplistic view of the world. This helps tominimize design time as well as reducing the possibility of error inimplementation.

The general operation of the state machine is to generate sets ofcycles:

-   -   Cycle 0: Fetch cycle. This is where the opcode is fetched from        the program memory, and the effective address from the fetched        opcode is generated.    -   Cycle 1: Execute cycle. This is where the operand is        (potentially) looked up via the generated effective address        (from Cycle 0) and the operation itself is executed.

Under normal conditions, the state machine generates cycles: 0, 1, 0, 1,0, 1, 0, 1 . . . . However, in some cases, the state machine stalls,generating Cycle 0 each clock tick until the stall condition finishes.Stall conditions include waiting for erase cycles of Flash memory,waiting for clients to read or write serial information, or an invalidopcode (due to tampering). If the Flash memory is currently beingerased, the next instruction cannot execute until the Flash memory hasfinished being erased. This is determined by the Wait signal coming fromthe Memory Unit. If Wait=1, the State Machine must only generate Cycle0s. There are also two cases for stalling due to serial I/O operations:

-   -   The opcode is ROR OutBit, and OutBitValid already=1. This means        that the current operation requires outputting a bit to the        client, but the client hasn't read the last bit yet.    -   The operation is ROR InBit, and InBitValid=0. This means that        the current operation requires reading a bit from the client,        but the client hasn't supplied the bit yet.

In both these cases, the state machine must stall until the stallingcondition has finished. The next “cycle” therefore depends on the old orprevious cycle, and the current values of CMD, Wait, OutBitValid, andInBitValid. Wait comes from the MU, and OutBitValid and InBitValid comefrom the I/O Unit. When Cycle is 0, the 8-bit op-code is fetched fromthe memory unit and placed in the 8-bit CMD register. The write enablefor the CMD register is therefore Cycle. There are two outputs from thisunit: Cycle and CMD. Both of these values are passed into all the otherprocessing units within the Authentication Chip. The 1-bit Cycle valuelets each unit know whether a fetch or execute cycle is taking place,while the 8-bit CMD value allows each unit to take appropriate actionfor commands related to the specific unit.

FIG. 187 shows the data flow and relationship between components of theState Machine where:

Logic₁: Wait OR ~(Old OR ((CMD=ROR) & ((CMD=InBit AND ~InBitValid) OR(CMD=OutBit AND OutBitValid))))

Old and CMD are both cleared to 0 upon a RESET. This results in thefirst cycle being 1, which causes the 0 CMD to be executed. 0 istranslated as TBR 0, which means branch to the address stored in addressoffset 0 if the Accumulator=0. Since the Accumulator is also cleared to0 on a RESET, the test will be true, so the net effect is a jump to theaddress stored in the 0th entry in the jump table. The two VAL units aredesigned to validate the data that passes through them. Each contains anOK bit connected to both Tamper Prevention and Detection Lines. The OKbit is set to 1 on RESET, and ORed with the ChipOK values from bothTamper Detection Lines each cycle. The OK bit is ANDed with each databit that passes through the unit. In the case of VAL₁, the effectiveCycle will always be 0 if the chip has been tampered with. Thus noprogram code will execute since there will never be a Cycle 1. There isno need to check if Old has been tampered with, for if an attackerfreezes the Old state, the chip will not execute any furtherinstructions. In the case of VAL₂, the effective 8-bit CMD value willalways be 0 if the chip has been tampered with, which is the TBR 0instruction. This will stop execution of any program code. VAL₂ alsoperforms a parity check on the bits from CMD to ensure that CMD has notbeen tampered with. If the parity check fails, the Erase TamperDetection Line is triggered.

I/O Unit

The I/O Unit is responsible for communicating serially with the outsideworld. The Authentication Chip acts as a slave serial device, acceptingserial data from a client, processing the command, and sending theresultant data to the client serially. The I/O Unit can be implementedwith regular CMOS, since the key does not pass through this unit. Itdoes not have to be implemented with non-flashing CMOS. In addition,none of the latches need to be parity checked since there is noadvantage for an attacker to destroy or modify them. The I/O Unitoutputs 0s and inputs 0s if either of the Tamper Detection Lines isbroken. This will only come into effect if an attacker has disabled theRESET and/or erase circuitry, since breaking either Tamper DetectionLines should result in a RESET or the erasure of all Flash memory

The InBit, InBitValid, OutBit, and OutBitValid 1 bit registers are usedfor communication between the client (System) and the AuthenticationChip. InBit and InBitValid provide the means for clients to passcommands and data to the Authentication Chip. OutBit and OutBitValidprovide the means for clients to get information from the AuthenticationChip. When the chip is RESET, InBitValid and OutBitValid are bothcleared. A client sends commands and parameter bits to theAuthentication Chip one bit at a time. From the Authentication Chip'spoint of view:

-   -   Reads from InBit will hang while InBitValid is clear. InBitValid        will remain clear until the client has written the next input        bit to InBit. Reading InBit clears the InBitValid bit to allow        the next InBit to be read from the client. A client cannot write        a bit to the Authentication Chip unless the InBitValid bit is        clear.    -   Writes to OutBit will hang while OutBitValid is set. OutBitValid        will remain set until the client has read the bit from OutBit.        Writing OutBit sets the OutBitValid bit to allow the next OutBit        to be read by the client. A client cannot read a bit from the        Authentication Chip unless the OutBitValid bit is set.

The actual stalling of commands is taken care of by the State Machine,but the various communication registers and the communication circuitryis found in the I/O Unit.

FIG. 188 shows the data flow and relationship between components of theI/O Unit where:

Logic₁: Cycle AND (CMD = ROR OutBit)

The Serial I/O unit contains the circuitry for communicating externallywith the external world via the Data pin. The InBitUsed control signalmust be set by whichever unit consumes the InBit during a given clockcycle (which can be any state of Cycle). The two VAL units arevalidation units connected to the Tamper Prevention and Detectioncircuitry, each with an OK bit. The OK bit is set to 1 on RESET, andORed with the ChipOK values from both Tamper Detection Lines each cycle.The OK bit is ANDed with each data bit that passes through the unit.

In the case of VAL₁, the effective bit output from the chip will alwaysbe 0 if the chip has been tampered with. Thus no useful output can begenerated by an attacker. In the case of VAL₂, the effective bit inputto the chip will always be 0 if the chip has been tampered with. Thus nouseful input can be chosen by an attacker. There is no need to verifythe registers in the I/O Unit since an attacker does not gain anythingby destroying or modifying them.

ALU

FIG. 189 illustrates a schematic block diagram of the Arithmetic LogicUnit. The Arithmetic Logic Unit (ALU) contains a 32-bit Acc(Accumulator) register as well as the circuitry for simple arithmeticand logical operations. The ALU and all sub-units must be implementedwith non-flashing CMOS since the key passes through it. In addition, theAccumulator must be parity-checked. The logic and registers contained inthe ALU must be covered by both Tamper Detection Lines. This is toensure that keys and intermediate calculation values cannot be changedby an attacker. A 1-bit Z register contains the state of zero-ness ofthe Accumulator. Both the Z and Accumulator registers are cleared to 0upon a RESET. The Z register is updated whenever the Accumulator isupdated, and the Accumulator is updated for any of the commands: LD,LDK, LOG, XOR, ROR, RPL, and ADD. Each arithmetic and logical blockoperates on two 32-bit inputs: the current value of the Accumulator, andthe current 32-bit output of the MU. Where:

Logic₁: Cycle AND CMD₇ AND (CMD⁶⁻⁴ ≠ ST)

Since the WriteEnables of Acc and Z takes CMD₇ and Cycle into account(due to Logic₁), these two bits are not required by the multiplexor MX₁in order to select the output. The output selection for MX₁ onlyrequires bits 6-3 of CMD and is therefore simpler as a result.

Output CMD⁶⁻³ MX₁ ADD ADD AND LOG AND OR LOG OR XOR XOR RPL RPL ROR RORFrom MU LD or LDK

The two VAL units are validation units connected to the TamperPrevention and Detection circuitry, each with an OK bit. The OK bit isset to 1 on RESET, and ORed with the ChipOK values from both TamperDetection Lines each cycle. The OK bit is ANDed with each data bit thatpasses through the unit. In the case of VAL₁, the effective bit outputfrom the Accumulator will always be 0 if the chip has been tamperedwith. This prevents an attacker from processing anything involving theAccumulator. VAL₁ also performs a parity check on the Accumulator,setting the Erase Tamper Detection Line if the check fails. In the caseof VAL₂, the effective Z status of the Accumulator will always be trueif the chip has been tampered with. Thus no looping constructs can becreated by an attacker. The remaining function blocks in the ALU aredescribed as follows. All must be implemented in non-flashing CMOS.

Block Description OR Takes the 32-bit output from the multiplexor MX₁,ORs all 32 bits together to get 1 bit. ADD Outputs the result of theaddition of its two inputs, modulo 2³². AND Outputs the 32-bit result ofa parallel bitwise AND of its two 32- bit inputs. OR Outputs the 32-bitresult of a parallel bitwise OR of its two 32- bit inputs. XOR Outputsthe 32-bit result of a parallel bitwise XOR of its two 32- bit inputs.RPL Examined in further detail below. ROR Examined in further detailbelow.

RPL

FIG. 190 illustrates a schematic block diagram of the RPL unit. The RPLunit is a component within the ALU. It is designed to implement theRPLCMP functionality of the Authentication Chip. The RPLCMP command isspecifically designed for use in secure writing to Flash memory M, basedupon the values in AccessMode. The RPL unit contains a 32-bit shiftregister called AMT (AccessModeTemp), which shifts right two bits eachshift pulse, and two 1-bit registers called EE and DE, directly basedupon the WR pseudocode's EqEncountered and DecEncountered flags. Allregisters are cleared to 0 upon a RESET. AMT is loaded with the 32 bitAM value (via the Accumulator) with a RPL INIT command, and EE and DEare set according to the general write algorithm via calls to RPL MHIand RPL MLO. The EQ and LT blocks have functionality exactly asdocumented in the WR command pseudocode. The EQ block outputs 1 if the 216-bit inputs are bit-identical and 0 if they are not. The LT blockoutputs 1 if the upper 16-bit input from the Accumulator is less thanthe 16-bit value selected from the MU via MX₂. The comparison isunsigned. The bit patterns for the operands are specifically chosen tomake the combinatorial logic simpler. The bit patterns for the operandsare listed again here since we will make use of the patterns:

Operand CMD³⁻⁰ Init 0000 MLO 1110 MHI 1111

The MHI and MLO have the hi bit set to easily differentiate them fromthe Init bit pattern, and the lowest bit can be used to differentiatebetween MHI and MLO. The EE and DE flags must be updated each time theRPL command is issued. For the Init stage, we need to setup the twovalues with 0, and for MHI and MLO, we need to update the values of EEand DE appropriately. The WriteEnable for EE and DE is therefore:

Logic₁: Cycle AND (CMD⁷⁻⁴ = RPL)

With the 32 bit AMT register, we want to load the register with thecontents of AM (read from the MU) upon an RPL Init command, and to shiftthe AMT register right two bit positions for the RPL MLO and RPL MHIcommands. This can be simply tested for with the highest bit of the RPLoperand (CMD₃). The WriteEnable and ShiftEnable for the AMT register istherefore:

Logic₂ Logic₁ AND CMD₃ Logic₃ Logic₁ AND ~CMD₃

The output from Logic₃ is also useful as input to multiplexor MX₁, sinceit can be used to gate through either the current 2 access mode bits or00 (which results in a reset of the DE and EE registers since itrepresents the access mode RW). Consequently MX₁ is:

Output Logic₃ MX₁ AMT output 0 00 1

The RPL logic only replaces the upper 16 bits of the Accumulator. Thelower 16 bits pass through untouched. However, of the 32 bits from theMU (corresponding to one of M[0-15]), only the upper or lower 16 bitsare used. Thus MX₂ tests CMD₀ to distinguish between MHI and MLO.

Output CMD₀ MX₂ Lower 16 bits 0 Upper 16 bits 1

The logic for updating the DE and EE registers matches the pseudocode ofthe WR command. Note that an input of an AccessMode value of 00 (=RWwhich occurs during an RPL INIT) causes both DE and EE to be loaded with0 (the correct initialization value). EE is loaded with the result fromLogic₄, and DE is loaded with the result fromLogic₅.

Logic₄ (((AccessMode=MSR) AND EQ) OR  ((AccessMode=NMSR) AND EE AND EQ))Logic₅ (((AccessMode=MSR) AND LT) OR  ((AccessMode=NMSR) AND DE) OR ((AccessMode=NMSR) AND EQ AND LT))

The upper 16 bits of the Accumulator must be replaced with the valuethat is to be written to M. Consequently Logic₆ matches the WE flag fromthe WR command pseudocode.

Logic₆ ((AccessMode=RW) OR  ((AccessMode=MSR) AND LT) OR ((AccessMode=NMSR) AND (DE OR LT)))

The output from Logic₆ is used directly to drive the selection betweenthe original 16 bits from the Accumulator and the value from M[0-15] viamultiplexor MX₃. If the 16 bits from the Accumulator are selected(leaving the Accumulator unchanged), this signifies that the Accumulatorvalue can be written to M[n]. If the 16-bit value from M is selected(changing the upper 16 bits of the Accumulator), this signifies that the16-bit value in M will be unchanged. MX₃ therefore takes the followingform:

Output Logic₆ MX₃ 16 bits from MU 0 16 bits from Acc 1

There is no point parity checking AMT as an attacker is better offforcing the input to MX₃ to be 0 (thereby enabling an attacker to writeany value to M). However, if an attacker is going to go to the troubleof laser-cutting the chip (including all Tamper Detection tests andcircuitry), there are better targets than allowing the possibility of alimited chosen-text attack by fixing the input of MX₃.

ROR

FIG. 191 illustrates a schematic block diagram of the ROR block of theALU. The ROR unit is a component within the ALU. It is designed toimplement the ROR functionality of the Authentication Chip. A 1-bitregister named RTMP is contained within the ROR unit. RTMP is cleared to0 on a RESET, and set during the ROR RB and ROR XRB commands. The RTMPregister allows implementation of Linear Feedback Shift Registers withany tap configuration. The XOR block is a 2 single-bit input, 1-bit outXOR. The RORn, blocks are shown for clarity, but in fact would behardwired into multiplexor MX₃, since each block is simply a rewiring ofthe 32-bits, rotated right N bits. All 3 multiplexors (MX₁, MX₂, andMX₃) depend upon the 8-bit CMD value. However, the bit patterns for theROR op-code are arranged for logic optimization purposes. The bitpatterns for the operands are listed again here since we will make useof the patterns:

Operand CMD³⁻⁰ InBit 0000 OutBit 0001 RB 0010 XRB 0011 IST 0100 ISW 0101MTRZ 0110  1 0111  2 1001 27 1010 31 1100

Logic₁ is used to provide the WriteEnable signal to RTMP. The RTMPregister should only be written to during ROR RB and ROR XRB commands.Logic₂ is used to provide the control signal whenever the InBit isconsumed. The two combinatorial logic blocks are:

Logic₁: Cycle AND (CMD⁷⁻⁴ = ROR) AND (CMD³⁻¹ = 001) Logic₂: Cycle AND(CMD⁷⁻⁰ = ROR InBit)

With multiplexor MX₁, we are selecting the bit to be stored in RTMP.Logic₁ already narrows down the CMD inputs to one of RB and XRB. We cantherefore simply test CMD₀ to differentiate between the two. Thefollowing table expresses the relationship between CMD₀ and the valueoutput from MX₁.

Output CMD₀ MX₁ Acc₀ 0 XOR output 1

With multiplexor MX₂, we are selecting which input bit is going toreplace bit 0 of the Accumulator input. We can only perform a smallamount of optimization here, since each different input bit typicallyrelates to a specific operand. The following table expresses therelationship between CMD₃₋₀ and the value output from MX₂.

Output CMD³⁻⁰ Comment MX₂ Acc₀ 1xxx OR 111 1, 2, 27, 31 RTMP 001x RB,XRB InBit 000x InBit, OutBit MU₀ 010x IST, ISW MTRZ 110 MTRZ

The final multiplexor, MX₃, does the final rotating of the 32-bit value.Again, the bit patterns of the CMD operand are taken advantage of:

Output CMD³⁻⁰ Comment MX₃ ROR 1 0xxx All except 2, 27, and 31 ROR 2 1xx1 2 ROR 27 1x1x 27 ROR 31 11xx 31

MinTicks Unit

FIG. 192 shows the data flow and relationship between components of theMinTicks Unit. The MinTicks Unit is responsible for a programmableminimum delay (via a countdown) between key-based operations within theAuthentication Chip. The logic and registers contained in theMinTicksUnit must be covered by both Tamper Detection Lines. This is toensure that an attacker cannot change the time between calls tokey-based functions. Nearly all of the MinTicks Unit can be implementedwith regular CMOS, since the key does not pass through most of thisunit. However the Accumulator is used in the SET MTR instruction.Consequently this tiny section of circuitry must be implemented innon-flashing CMOS. The remainder of the MinTicks Unit does not have tobe implemented with non-flashing CMOS. However, the MTRZ latch (seebelow) needs to be parity checked.

The MinTicks Unit contains a 32-bit register named MTR(MinTicksRemaining) The MTR register contains the number of clock ticksremaining before the next key-based function can be called. Each cycle,the value in MTR is decremented by 1 until the value is 0. Once MTR hits0, it does not decrement any further. An additional one-bit registernamed MTRZ (MinTicksRegisterZero) reflects the current zero-ness of theMTR register. MTRZ is 1 if the MTRZ register is 0, and MTRZ is 0 if theMTRZ register is not 0. The MTR register is cleared by a RESET, and setto a new count via the SET MTR command, which transfers the currentvalue in the Accumulator into the MTR register.

Where: Logic₁ CMD = SET MTR And: Output Logic₁ MTRZ MX₁ Acc 1 — MTR − 10 0 0 0 1

Since Cycle is connected to the WriteEnables of MTR and MTRZ, theseregisters only update during the Execute cycle, i.e. when Cycle=1. Thetwo VAL units are validation units connected to the Tamper Preventionand Detection circuitry, each with an OK bit. The OK bit is set to 1 onRESET, and ORed with the ChipOK values from both Tamper Detection Lineseach cycle. The OK bit is ANDed with each data bit that passes throughthe unit. In the case of VAL₁, the effective output from MTR is 0, whichmeans that the output from the decrementor unit is all 1s, therebycausing MTRZ to remain 0, thereby preventing an attacker from using thekey-based functions. VAL₁ also validates the parity of the MTR register.If the parity check fails, the Erase Tamper Detection Line is triggered.In the case of VAL₂, if the chip has been tampered with, the effectiveoutput from MTRZ will be 0, indicating that the MinTicksRemainingregister has not yet reached 0, thereby preventing an attacker fromusing the key-based functions.

Program Counter Unit

FIG. 192 is a block diagram of the Program Counter Unit. The ProgramCounter Unit (PCU) includes the 9 bit PC (Program Counter), as well aslogic for branching and subroutine control. The Program Counter Unit canbe implemented with regular CMOS, since the key does not pass throughthis unit. It does not have to be implemented with non-flashing CMOS.However, the latches need to be parity-checked. In addition, the logicand registers contained in the Memory Unit must be covered by bothTamper Detection Lines to ensure that the PC cannot be changed by anattacker. The PC is actually implemented as a 6-level by 9-bit PCA (PCArray), indexed by the 3-bit SP (Stack Pointer) register. The PC and SPregisters are all cleared to 0 on a RESET, and updated during the flowof program control according to the opcodes. The current value for thePC is output to the MU during Cycle 0 (the Fetch cycle). The PC isupdated during Cycle 1 (the Execute cycle) according on the commandbeing executed. In most cases, the PC simply increments by 1. However,when branching occurs (due to subroutine or some other form of jump),the PC is replaced by a new value. The mechanism for calculating the newPC value depends upon the opcode being processed. The ADD block is asimple adder modulo 2⁹. The inputs are the PC value and either 1 (forincrementing the PC by 1) or a 9 bit offset (with hi bit set and lower 8bits from the MU). The “+1” block takes a 3-bit input and increments itby 1 (with wrap). The “−1” block takes a 3-bit input and decrements itby 1 (with wrap). The different forms of PC control are as follows:

Command Action JSR, Save old value of PC onto stack for later. JSI (ACC)New PC is 9 bit value where bit0 = 0 (subroutines must therefore startat an even address), and upper 8 bits of address come from MU (MU 8-bitvalue is Jump Table 1 for JSR, and Jump Table 2 for JSI) JSI RTS Pop oldvalue of PC from stack and increment by 1 to get new PC. TBR If the Zflag matches the TRB test, replace PC by 9 bit value where bit0 = 0 andupper 8 bits come from MU. Otherwise increment current PC by 1. DBR C1,Add 9 bit offset (8 bit value from MU and hi bit = 1) to DBR C2 currentPC only if the C1Z or C2Z is set (C1Z for DBR C1, C2Z for DBR C2).Otherwise increment current PC by 1. All others Increment current PC by1.

Since the same action takes place for JSR, and JSI (ACC), wespecifically detect that case in Logic₁. By the same concept, we canspecifically test for the JSI RTS case in Logic₂.

Logic₁ (CMD⁷⁻⁵ = 001) OR (CMD⁷⁻³ = 01001) Logic₂ CMD⁷⁻³ = 01000

When updating the PC, we must decide if the PC is to be replaced by acompletely new item, or by the result of the adder. This is the case forJSR and JSI (ACC), as well as TBR as long as the test bit matches thestate of the Accumulator. All but TBR is tested for by Logic₁, so Logic₃also includes the output of Logic₁ as its input. The output from Logic₃is then used by multiplexors MX₂ to obtain the new PC value.

Logic₃ Logic₁ OR ((CMD⁷⁻⁴ = TBR) AND (CMD₃ XOR Z)) Output Logic₃ MX₂Output from Adder 0 Replacement value 1

The input to the 9-bit adder depends on whether we are incrementing by 1(the usual case), or adding the offset as read from the MU (the DBRcommand). Logic₄ generates the test. The output from Logic₄ is thendirectly used by multiplexor MX₃ accordingly.

Logic₄ ((CMD⁷⁻³ = DBR C1) AND C1Z) OR (CMD⁷⁻³ = DBR C2) AND C2Z)) OutputLogic₄ MX₃ Output from Adder 0 Replacement value 1

Finally, the selection of which PC entry to use depends on the currentvalue for SP. As we enter a subroutine, the SP index value mustincrement, and as we return from a subroutine, the SP index value mustdecrement. In all other cases, and when we want to fetch a command(Cycle 0), the current value for the SP must be used. Logic₁ tells uswhen a subroutine is being entered, and Logic₂ tells us when thesubroutine is being returned from. The multiplexor selection istherefore defined as follows:

Output Cycle/Logic₁/Logic₂ MX₁ SP − 1 1x1 SP + 1 11x SP 0xx OR 00

The two VAL units are validation units connected to the TamperPrevention and Detection circuitry), each with an OK bit. The OK bit isset to 1 on RESET, and ORed with the ChipOK values from both TamperDetection Lines each cycle. The OK bit is ANDed with each data bit thatpasses through the unit. Both VAL units also parity-check the data bitsto ensure that they are valid. If the parity-check fails, the EraseTamper Detection Line is triggered. In the case of VAL_(i), theeffective output from the SP register will always be 0. If the chip hasbeen tampered with. This prevents an attacker from executing anysubroutines. In the case of VAL₂, the effective PC output will always be0 if the chip has been tampered with. This prevents an attacker fromexecuting any program code.

Memory Unit

The Memory Unit (MU) contains the internal memory of the AuthenticationChip. The internal memory is addressed by 9 bits of address, which ispassed in from the Address Generator Unit. The Memory Unit outputs theappropriate 32-bit and 8-bit values according to the address. The MemoryUnit is also responsible for the special Programming Mode, which allowsinput of the program Flash memory. The contents of the entire MemoryUnit must be protected from tampering. Therefore the logic and registerscontained in the Memory Unit must be covered by both Tamper DetectionLines. This is to ensure that program code, keys, and intermediate datavalues cannot be changed by an attacker. All Flash memory needs to bemulti-state, and must be checked upon being read for invalid voltages.The 32-bit RAM also needs to be parity-checked. The 32-bit data pathsthrough the Memory Unit must be implemented with non-flashing CMOS sincethe key passes along them. The 8-bit data paths can be implemented inregular CMOS since the key does not pass along them.

Constants

The Constants memory region has address range: 000000000-000001111. Itis therefore the range 00000xxxx. However, given that the next 48addresses are reserved, this can be taken advantage of during decoding.The Constants memory region can therefore be selected by the upper 3bits of the address (Adr₈₋₆=000), with the lower 4 bits fed intocombinatorial logic, with the 4 bits mapping to 32-bit output values asfollows:

Adr³⁻⁰ Output Value 0000 0x00000000 0001 0x36363636 0010 0x5C5C5C5C 00110xFFFFFFFF 0100 0x5A827999 0101 0x6ED9EBA1 0110 0x8F1BBCDC 01110xCA62C1D6 1000 0x67452301 1001 0xEFCDAB89 1010 0x98BADCFE 10110x10325476 11xx 0xC3D2E1F0

RAM

The address space for the 32 entry 32-bit RAM is 001000000-001011111. Itis therefore the range 0010xxxxx. The RAM memory region can therefore beselected by the upper 4 bits of the address (Adr₈₋₅=0010), with thelower 5 bits selecting which of the 32 values to address. Given thecontiguous 32-entry address space, the RAM can easily be implemented asa simple 32×32-bit RAM. Although the CPU treats each address from therange 00000-11111 in special ways, the RAM address decoder itself treatsno address specially. All RAM values are cleared to 0 upon a RESET,although any program code should not take this for granted.

Flash Memory—Variables

The address space for the 32-bit wide Flash memory is001100000-001111111. It is therefore the range 0011xxxxx. The Flashmemory region can therefore be selected by the upper 4 bits of theaddress (Adr₈₋₅=0111), with the lower 5 bits selecting which value toaddress. The Flash memory has special requirements for erasure. It takesquite some time for the erasure of Flash memory to complete. The Waitsignal is therefore set inside the Flash controller upon receipt of aCLR command, and is only cleared once the requested memory has beenerased. Internally, the erase lines of particular memory ranges are tiedtogether, so that only 2 bits are required as indicated by the followingtable:

Adr⁴⁻³ Erases range 00 R₀₋₄ 01 MT, AM, K1₀₋₄, K2₀₋₄ 10 Individual Maddress (Adr) 11 IST, ISW

Flash values are unchanged by a RESET, although program code should nottake the initial values for Flash (after manufacture) other thangarbage. Operations that make use of Flash addresses are LD, ST, ADD,RPL, ROR, CLR, and SET. In all cases, the operands and the memoryplacement are closely linked, in order to minimize the addressgeneration and decoding. The entire variable section of Flash memory isalso erased upon entering Programming Mode, and upon detection of adefinite physical Attack.

Flash Memory—Program

The address range for the 384 entry 8-bit wide program Flash memory is010000000-111111111. It is therefore the range 01xxxxxxx-11xxxxxxx.Decoding is straightforward given the ROM start address and addressrange. Although the CPU treats parts of the address range in specialways, the address decoder itself treats no address specially. Flashvalues are unchanged by a RESET, and are cleared only by enteringProgramming Mode. After manufacture, the Flash contents must beconsidered to be garbage. The 384 bytes can only be loaded by the Statemachine when in Programming Mode.

Block Diagram of MU

FIG. 193 is a block diagram of the Memory Unit. The logic shown takesadvantage of the fact that 32-bit data and 8-bit data are required byseparate commands, and therefore fewer bits are required for decoding.As shown, 32-bit output and 8-bit output are always generated. Theappropriate components within the remainder of the Authentication Chipsimply use the 32-bit or 8-bit value depending on the command beingexecuted. Multiplexor MX₁, selects the 32-bit output from a choice ofTruth Table constants, RAM, and Flash memory. Only 2 bits are requiredto select between these 3 outputs, namely Adr₆ and Adr₅. Thus MX₂ takesthe following form:

Output Adr⁶⁻⁵ MX₂ Output from 32-bit Truth Table 00 Output from 32-bitFlash memory 10 Output from 32-bit RAM 11

The logic for erasing a particular part of the 32-bit Flash memory issatisfied by Logic₁. The Erase Part control signal should only be setduring a CLR command to the correct part of memory while Cycle=1. Notethat a single CLR command may clear a range of Flash memory. Adr₆ issufficient as an address range for CLR since the range will always bewithin Flash for valid operands, and 0 for non-valid operands. Theentire range of 32-bit wide Flash memory is erased when the EraseDetection Lines is triggered (either by an attacker, or by deliberatelyentering Programming Mode).

Logic₁ Cycle AND (CMD⁷⁻⁴ = CLR) AND Adr₆

The logic for writing to a particular part of Flash memory is satisfiedby Logic₂. The WriteEnable control signal should only be set during anappropriate ST command to a Flash memory range while Cycle=1. Testingonly Adr₆₋₅ is acceptable since the ST command only validly writes toFlash or RAM (if Adr₆₋₅ is 00, K2MX must be 0).

Logic₂ Cycle AND (CMD⁷⁻⁴ = ST) AND (Adr⁶⁻⁵ = 10)

The WE (WriteEnable) flag is set during execution of the SET WE and CLRWE commands. Logic₃ tests for these two cases. The actual bit written toWE is CMD₄.

Logic₃ Cycle AND (CMD⁷⁻⁵ = 011) AND (CMD³⁻⁰ = 0000)

The logic for writing to the RAM region of memory is satisfied byLogic₄. The WriteEnable control signal should only be set during anappropriate ST command to a RAM memory range while Cycle=1. However thisis tempered by the WE flag, which governs whether writes to X[N] arepermitted. The X[N] range is the upper half of the RAM, so this can betested for using Adr₄. Testing only Adr₆₋₅ as the full address range ofRAM is acceptable since the ST command only writes to Flash or RAM.

Logic₄ Cycle AND (CMD⁷⁻⁴ = ST) AND (Adr⁶⁻⁵ = 11) AND ((Adr₄ AND WE) OR(~Adr₄))

The three VAL units are validation units connected to the TamperPrevention and Detection circuitry, each with an OK bit. The OK bit isset to 1 on RESET, and ORed with the ChipOK values from both TamperDetection Lines each cycle. The OK bit is ANDed with each data bit thatpasses through the unit. The VAL units also check the data bits toensure that they are valid. VAL₁ and VAL₂ validate by checking the stateof each data bit, and VAL₃ performs a parity check. If any validity testfails, the Erase Tamper Detection Line is triggered. In the case ofVAL₁, the effective output from the program Flash will always be 0(interpreted as TBR 0) if the chip has been tampered with. This preventsan attacker from executing any useful instructions. In the case of VAL₂,the effective 32-bit output will always be 0 if the chip has beentampered with. Thus no key or intermediate storage value is available toan attacker. The 8-bit Flash memory is used to hold the program code,jump tables and other program information. The 384 bytes of ProgramFlash memory are selected by the full 9 bits of address (using addressrange 01xxxxxxx-11xxxxxxx). The Program Flash memory is erased only whenthe Erase Detection Lines is triggered (either by an attacker, or byentering Programming Mode due to the Programming Mode Detection Unit).When the Erase Detection Line is triggered, a small state machine in theProgram Flash Memory Unit erases the 8-bit Flash memory, validates theerasure, and loads in the new contents (384 bytes) from the serialinput. The following pseudocode illustrates the state machine logic thatis executed when the Erase Detection line is triggered:

Set WAIT output bit to prevent the remainder of the chip fromfunctioning Fix 8-bit output to be 0 Erase all 8-bit Flash memory Temp ←0 For Adr = 0 to 383  Temp ← Temp OR Flash_(Adr) IF (Temp ≠ 0)  Hang ForAdr = 0 to 383  Do 8 times       Wait for InBitValid to be set      ShiftRight[Temp, InBit]  Set InBitUsed control signal  Flash_(Adr)← Temp Hang

During the Programming Mode state machine execution, 0 must be placedonto the 8-bit output. A 0 command causes the remainder of theAuthentication chip to interpret the command as a TBR 0. When the chiphas read all 384 bytes into the Program Flash Memory, it hangs (loopsindefinitely). The Authentication Chip can then be reset and the programused normally. Note that the erasure is validated by the same 8-bitregister that is used to load the new contents of the 8-bit programFlash memory. This helps to reduce the chances of a successful attack,since program code can't be loaded properly if the register used tovalidate the erasure is destroyed by an attacker. In addition, theentire state machine is protected by both Tamper Detection lines.

Address Generator Unit

The Address Generator Unit generates effective addresses for accessingthe Memory Unit (MU). In Cycle 0, the PC is passed through to the MU inorder to fetch the next opcode. The Address Generator interprets thereturned opcode in order to generate the effective address for Cycle 1.In Cycle 1, the generated address is passed to the MU. The logic andregisters contained in the Address Generator Unit must be covered byboth Tamper Detection Lines. This is to ensure that an attacker cannotalter any generated address. Nearly all of the Address Generator Unitcan be implemented with regular CMOS, since the key does not passthrough most of this unit. However 5 bits of the Accumulator are used inthe JSI Address generation. Consequently this tiny section of circuitrymust be implemented in non-flashing CMOS. The remainder of the AddressGenerator Unit does not have to be implemented with non-flashing CMOS.However, the latches for the counters and calculated address should beparity-checked. If either of the Tamper Detection Lines is broken, theAddress Generator Unit will generate address 0 each cycle and allcounters will be fixed at 0. This will only come into effect if anattacker has disabled the RESET and/or erase circuitry, since undernormal circumstances, breaking a Tamper Detection Line will result in aRESET or the erasure of all Flash memory.

Background to Address Generation

The logic for address generation requires an examination of the variousopcodes and operand combinations. The relationship betweenopcode/operand and address is examined in this section, and is used asthe basis for the Address Generator Unit.

Constants

The lower 4 entries are the simple constants for general-purpose use aswell as the HMAC algorithm. The lower 4 bits of the LDK operand directlycorrespond to the lower 3 bits of the address in memory for these 4values, i.e. 0000, 0001, 0010, and 0011 respectively. The y constantsand the h constants are also addressed by the LDK command. However theaddress is generated by ORing the lower 3 bits of the operand with theinverse of the C1 counter value, and keeping the 4th bit of the operandintact. Thus for LDK y, the y operand is 0100, and with LDK h, the hoperand is 1000. Since the inverted Cl value takes on the range 000-011for y, and 000-100 for h, the ORed result gives the exact address. Forall constants, the upper 5 bits of the final address are always 00000.

RAM

Variables A-T have addresses directly related to the lower 3 bits oftheir operand values. That is, for operand values 0000-0101 of the LD,ST, ADD, LOG, and XOR commands, as well as operand vales 1000-1101 ofthe LOG command, the lower 3 operand address bits can be used togetherwith a constant high 6-bit address of 001000 to generate the finaladdress. The remaining register values can only be accessed via anindexed mechanism. Variables A-E, B160, and H are only accessible asindexed by the C1 counter value, while X is indexed by N₁, N₂, N₃, andN₄. With the LD, ST and ADD commands, the address for AE as indexed byCl can be generated by taking the lower 3 bits of the operand (000) andORing them with the Cl counter value. However, H and B160 addressescannot be generated in this way, (otherwise the RAM address space wouldbe non-contiguous). Therefore simple combinatorial logic must convert AEinto 0000, H into 0110, and B160 into 1011. The final address can beobtained by adding Cl to the 4-bit value (yielding a 4-bit result), andprepending the constant high 5-bit address of 00100. Finally, the Xrange of registers is only accessed as indexed by N₁, N₂, N₃, and N₄.With the XOR command, any of N₁₋₄ can be used to index, while with LD,ST, and ADD, only N₄ can be used. Since the operand of X in LD, ST, andADD is the same as the X_(N4) operand, the lower 2 bits of the operandselects which N to use. The address can thus be generated as a constanthigh 5-bit value of 00101, with the lower 4 bits coming from by theselected N counter.

Flash Memory—Variables

The addresses for variables MT and AM can be generated from the operandsof associated commands. The 4 bits of operand can be used directly (0110and 0111), and prepending the constant high 5-bit address of 00110.Variables R₁₋₅, K1 ₁₋₅, K2 ₁₋₅, and M₀₋₇ are only accessible as indexedby the inverse of the Cl counter value (and additionally in the case ofR, by the actual Cl value). Simple combinatorial logic must convert Rand RF into 00000, K into 01000 or 11000 depending on in whether K1 orK2 is being addressed, and M (including MHI and MLO) into 10000. Thefinal address can be obtained by ORing (or adding) Cl (or in the case ofRF, using Cl directly) with the 5-bit value, and prepending the constanthigh 4-bit address of 0011. Variables IST and ISW are each only 1 bit ofvalue, but can be implemented by any number of bits. Data is read andwritten as either 0x00000000 or 0xFFFFFFFF. They are addressed only byROR, CLR and SET commands. In the case of ROR, the low bit of theoperand is combined with a constant upper 8-bits value of 00111111,yielding 001111110 and 001111111 for IST and ISW respectively. This isbecause none of the other ROR operands make use of memory, so in casesother than IST and ISW, the value returned can be ignored. With SET andCLR, IST and ISW are addressed by combining a constant upper 4-bits of0011 with a mapping from IST (0100) to 11110 and from ISW (0101) to11111. Since IST and ISW share the same operand values with E and T fromRAM, the same decoding logic can be used for the lower 5 bits. The finaladdress requires bits 4, 3, and 1 to be set (this can be done by ORingin the result of testing for operand values 010×).

Flash Memory—Program

The address to lookup in program Flash memory comes directly from the9-bit PC (in Cycle 0) or the 9-bit Adr register (in Cycle 1). Commandssuch as TBR, DBR, JSR and JSI modify the PC according to data stored intables at specific addresses in the program memory. As a result, addressgeneration makes use of some constant address components, with thecommand operand (or the Accumulator) forming the lower bits of theeffective address:

Constant (upper) Variable (lower) Command Address Range part of addresspart of address TBR 010000xxx 010000 CMD²⁻⁰ JSR 0100xxxxx 0100 CMD⁴⁻⁰JSI ACC 0101xxxxx 0101 Acc²⁻⁰ DBR 011000xxx 011000 CMD²⁻⁰

Block Diagram of Address Generator Unit

FIG. 194 shows a schematic block diagram for the Address Generator Unit.The primary output from the Address Generator Unit is selected bymultiplexor MX₁, as shown in the following table:

Output Cycle MX₁ PC 0 Adr 1

It is important to distinguish between the CMD data and the 8-bit datafrom the MU:

-   -   In Cycle 0, the 8-bit data line holds the next instruction to be        executed in the following Cycle 1. This 8-bit command value is        used to decode the effective address. By contrast, the CMD 8-bit        data holds the previous instruction, so should be ignored.    -   In Cycle 1, the CMD line holds the currently executing        instruction (which was in the 8-bit data line during Cycle 0),        while the 8-bit data line holds the data at the effective        address from the instruction. The CMD data must be executed        during Cycle 1.

Consequently, the choice of 9-bit data from the MU or the CMD value ismade by multiplexor MX3, as shown in the following table:

Output Cycle MX₃ 8-bit data from MU 0 CMD 1

Since the 9-bit Adr register is updated every Cycle 0, the WriteEnableof Adr is connected to ˜Cycle. The Counter Unit generates counters C1,C2 (used internally) and the selected N index. In addition, the CounterUnit outputs flags C1Z and C2Z for use by the Program Counter Unit. Thevarious *GEN units generate addresses for particular command typesduring Cycle 0, and multiplexor MX₂ selects between them based on thecommand as read from program memory via the PC (i.e. the 8-bit dataline). The generated values are as follows:

Commands for which Block address is generated JSIGEN JSI ACC JSRGEN JSR,TBR DBRGEN DBR LDKGEN LDK RPLGEN RPL VARGEN LD, ST, ADD, LOG, XOR BITGENROR, SET CLRGEN CLR

Multiplexor MX₂ has the following selection criteria:

8-bit data Output value from MU MX₂ 9-bit value from JSIGEN 01001xxx9-bit value from JSRGEN 001xxxxx OR 0000xxxx 9-bit value from DBRGEN0001xxxx 9-bit value from LDKGEN 1110xxxx 9 bit value from RPLGEN1101xxxx 9-bit value from VARGEN 10xxxxxx OR 1x11xxxx 9-bit value fromBITGEN 0111xxxx OR 1100xxxx 9 bit value from CLRGEN 0110xxxx

The VAL₁ unit is a validation unit connected to the Tamper Preventionand Detection circuitry. It contains an OK bit that is set to 1 onRESET, and ORed with the ChipOK values from both Tamper Detection Lineseach cycle. The OK bit is ANDed with the 9 bits of Effective Addressbefore they can be used. If the chip has been tampered with, the addressoutput will be always 0, thereby preventing an attacker from accessingother parts of memory. The VAL₁ unit also performs a parity check on theEffective Address bits to ensure it has not been tampered with. If theparity-check fails, the Erase Tamper Detection Line is triggered.

JSIGEN

FIG. 195 shows a schematic block diagram for the JSIGEN Unit. The JSIGENUnit generates addresses for the JSI ACC instruction. The effectiveaddress is simply the concatenation of:

-   -   the 4-bit high part of the address for the JSI Table (0101) and    -   the lower 5 bits of the Accumulator value.

Since the Accumulator may hold the key at other times (when a jumpaddress is not being generated), the value must be hidden from sight.Consequently this unit must be implemented with non-flashing CMOS. Themultiplexor MX₁ simply chooses between the lower 5 bits from Accumulatoror 0, based upon whether the command is JSIGEN. Multiplexor MX₁ has thefollowing selection criteria:

Output CMD⁷⁻⁰ MX₁ Accumulator⁴⁻⁰ JSI ACC 00000 ~(JSI ACC)

JSRGEN

FIG. 196 shows a schematic block diagram for the JSRGEN Unit. The JSRGENUnit generates addresses for the JSR and TBR instructions. The effectiveaddress comes from the concatenation of:

-   -   the 4-bit high part of the address for the JSR table (0100),    -   the offset within the table from the operand (5 bits for JSR        commands, and 3 bits plus a constant 0 bit for TBR).        where Logic₁ produces bit 3 of the effective address. This bit        should be bit 3 in the case of JSR, and 0 in the case of TBR:

Logic₁ bit₅ AND bit₃

Since the JSR instruction has a 1 in bit 5, (while TBR is 0 for thisbit) ANDing this with bit 3 will produce bit 3 in the case of JSR, and 0in the case of TBR.

DBRGEN

FIG. 197 shows a schematic block diagram for the DBRGEN Unit. The DBRGENUnit generates addresses for the DBR instructions. The effective addresscomes from the concatenation of:

-   -   the 6-bit high part of the address for the DBR table (011000),        and    -   the lower 3 bits of the operand

LDKGEN

FIG. 198 shows a schematic block diagram for the LDKGEN Unit. The LDKGENUnit generates addresses for the LDK instructions. The effective addresscomes from the concatenation of:

-   -   the 5-bit high part of the address for the LDK table (00000),    -   the high bit of the operand, and    -   the lower 3 bits of the operand (in the case of the lower        constants), or the lower 3 bits of the operand ORed with Cl (in        the case of indexed constants).

The OR₂ block simply ORs the 3 bits of C1 with the 3 lowest bits fromthe 8-bit data output from the MU. The multiplexor MX₁ simply choosesbetween the actual data bits and the data bits ORed with Cl, based uponwhether the upper bits of the operand are set or not. The selector inputto the multiplexor is a simple OR gate, ORing bit₂ with bit₃.Multiplexor MX₁ has the following selection criteria:

Output bit₃ OR bit₂ MX₁ bit²⁻⁰ 0 Output from OR block 1

RPLGEN

FIG. 199 shows a schematic block diagram for the RPLGEN Unit. The RPLGENUnit generates addresses for the RPL instructions. When K2MX is 0, theeffective address is a constant 000000000. When K2MX is 1 (indicatingreads from M return valid values), the effective address comes from theconcatenation of:

-   -   the 6-bit high part of the address for M (001110), and    -   the 3 bits of the current value for Cl

The multiplexor MX₁ chooses between the two addresses, depending on thecurrent value of K2MX. Multiplexor MX₁ therefore has the followingselection criteria:

Output K2MX MX₁ 000000000 0 001110 | C1 1

VARGEN

FIG. 200 shows a schematic block diagram for the VARGEN Unit. The VARGENUnit generates addresses for the LD, ST, ADD, LOG, and XOR instructions.The K2MX 1-bit flag is used to determine whether reads from M are mappedto the constant 0 address (which returns 0 and cannot be written to),and which of K1 and K2 is accessed when the operand specifies K. The4-bit Adder block takes 2 sets of 4-bit inputs, and produces a 4-bitoutput via addition modulo 2⁴. The single bit register K2MX is only everwritten to during execution of a CLR K2MX or a SET K2MX instruction.Logic₁ sets the K2MX WriteEnable based on these conditions:

Logic₁ Cycle AND bit⁷⁻⁰ = 011x0001

The bit written to the K2MX variable is 1 during a SET instruction, and0 during a CLR instruction. It is convenient to use the low order bit ofthe opcode (bit₄) as the source for the input bit. During addressgeneration, a Truth Table implemented as combinatorial logic determinespart of the base address as follows:

bit⁷⁻⁴ bit³⁻⁰ Description Output Value LOG X A, B, C, D, E, T, MT, AM00000 ≠LOG 0xxx OR 1x00 A, B, C, D, E, T, MT, AM, 00000 AE[C1], R[C1]≠LOG 1001 B160 01011 ≠LOG 1010 H 00110 ≠LOG 111x X, M 10000 ≠LOG 1101 KK2MX | 1000

Although the Truth Table produces 5 bits of output, the lower 4 bits arepassed to the 4-bit Adder, where they are added to the index value (Cl,N or the lower 3 bits of the operand itself). The highest bit passes theadder, and is prepended to the 4-bit result from the adder result inorder to produce a 5-bit result. The second input to the adder comesfrom multiplexor MX_(i), which chooses the index value from Cl, N, andthe lower 3 bits of the operand itself). Although Cl is only 3 bits, thefourth bit is a constant 0. Multiplexor MX₁ has the following selectioncriteria:

Output bit⁷⁻⁰ MX₁ Data²⁻⁰ (bit₃=0) OR (bit⁷⁻⁴=LOG) C1 (bit₃=1) AND(bit²⁻⁰≠111) AND ((bit⁷⁻⁴=1x11) OR (bit⁷⁻⁴=ADD)) N ((bit₃=1) AND(bit⁷⁻⁴=XOR)) OR (((bit⁷⁻⁴=1x11) OR (bit⁷⁻⁴=ADD)) AND (bit³⁻⁰=1111))

The 6th bit (bit₅) of the effective address is 0 for RAM addresses, and1 for Flash memory addresses. The Flash memory addresses are MT, AM, R,K, and M. The computation for bit₅ is provided by Logic₂:

Logic₂ ((bit³⁻⁰=110) OR (bit³⁻⁰=011x) OR (bit³⁻⁰=110x)) AND((bit⁷⁻⁴=1x11) OR (bit⁷⁻⁴=ADD))

A constant 1 bit is prepended, making a total of 7 bits of effectiveaddress. These bits will form the effective address unless K2MX is 0 andthe instruction is LD, ADD or ST M[C1]. In the latter case, theeffective address is the constant address of 0000000. In both cases, two0 bits are prepended to form the final 9-bit address. The computation isshown here, provided by Logic₃ and multiplexor MX₂.

Logic₃ ~K2MX AND (bit³⁻⁰=1110) AND ((bit⁷⁻⁴=1x11) OR (bit⁷⁻⁴=ADD))Output Logic₃ MX₂ Calculated bits 0 0000000 1

CLRGEN

FIG. 201 shows a schematic block diagram for the CLRGEN Unit. The CLRGENUnit generates addresses for the CLR instruction. The effective addressis always in Flash memory for valid memory accessing operands, and is 0for invalid operands. The CLR M[C1] instruction always erases M[C1],regardless of the status of the K2MX flag (kept in the VARGEN Unit). TheTruth Table is simple combinatorial logic that implements the followingrelationship:

Input Value (bit³⁻⁰) Output Value 1100 00 1100 000 1101 00 1101 000 111000 1110 | C1 1111 00 1111 110 ~(11xx) 000000000

It is a simple matter to reduce the logic required for the Truth Tablesince in all 4 main cases, the first 6 bits of the effective address are00 followed by the operand (bits₃₋₀).

BITGEN

FIG. 202 shows a schematic block diagram for the BITGEN Unit. The BITGENUnit generates addresses for the ROR and SET instructions. The effectiveaddress is always in Flash memory for valid memory accessing operands,and is 0 for invalid operands. Since ROR and SET instructions onlyaccess the IST and ISW Flash memory addresses (the remainder of theoperands access registers), a simple combinatorial logic Truth Tablesuffices for address generation:

Input Value (bit³⁻⁰) Output Value 010x 00111111 | bit₀ ~(010x) 000000000

Counter Unit

Fig. Y37 shows a schematic block diagram for the Counter Unit. TheCounter Unit generates counters C1, C2 (used internally) and theselected N index. In addition, the Counter Unit outputs flags C1Z andC2Z for use externally. Registers C1 and C2 are updated when they arethe targets of a DBR or SC instruction. The high bit of the operand(bit₃ of the effective command) gives the selection between C1 and C2.Logic₁ and Logic₂ determine the WriteEnables for C1 and C2 respectively.

Logic₁ Cycle AND (bit⁷⁻³=0x010) Logic₂ Cycle AND (bit⁷⁻³=0x011)

The single bit flags C1Z and C2Z are produced by the NOR of theirmultibit C1 and C2 counterparts. Thus C1Z is 1 if C1=0, and C2Z is 1 ifC2=0. During a DBR instruction, the value of either C1 or C2 isdecremented by 1 (with wrap). The input to the Decrementor unit isselected by multiplexor MX₂ as follows:

Output bit₃ MX₂ C1 0 C2 1

The actual value written to C1 or C2 depends on whether the DBR or SCinstruction is being executed. Multiplexor MX₁ selects between theoutput from the Decrementor (for a DBR instruction), and the output fromthe Truth Table (for a SC instruction). Note that only the lowest 3 bitsof the 5-bit output are written to Cl. Multiplexor MX₁ therefore has thefollowing selection criteria:

Output bit₆ MX₁ Output from Truth Table 0 Output from Decrementor 1

The Truth Table holds the values to be loaded by C1 and C2 via the SCinstruction. The Truth Table is simple combinatorial logic thatimplements the following relationship:

Input Value (bit²⁻⁰) Output Value 000 00010 001 00011 010 00100 01100111 100 01010 101 01111 110 10011 111 11111

Registers N1, N2, N3, and N4 are updated by their next value−1 (withwrap) when they are referred to by the XOR instruction. Register N4 isalso updated when a ST X[N4] instruction is executed. LD and ADDinstructions do not update N4. In addition, all 4 registers are updatedduring a SET Nx command. Logic₄₋₇ generate the WriteEnables forregisters N1-N4. All use Logic₃, which produces a 1 if the command isSET Nx, or 0 otherwise.

Logic₃ bit⁷⁻⁰=01110010 Logic₄ Cycle AND ((bit⁷⁻⁰=10101000) OR Logic₃)Logic₅ Cycle AND ((bit⁷⁻⁰=10101001) OR Logic₃) Logic₆ Cycle AND((bit⁷⁻⁰=10101010) OR Logic₃) Logic₇ Cycle AND ((bit⁷⁻⁰=11111011) OR(bit⁷⁻⁰=10101011) OR Logic₃)

The actual N index value passed out, or used as the input to theDecrementor, is simply selected by multiplexor MX₄ using the lower 2bits of the operand:

Output bit¹⁻⁰ MX₄ N1 00 N2 01 N3 10 N4 11

The Incrementor takes 4 bits of input value (selected by multiplexorMX₄) and adds 1, producing a 4-bit result (due to addition modulo 2⁴).Finally, four instances of multiplexor MX₃ select between a constantvalue (different for each N, and to be loaded during the SET Nxcommand), and the result of the Decrementor (during XOR or STinstructions). The value will only be written if the appropriateWriteEnable flag is set (see Logic₄-Logic₇), so Logic₃ can safely beused for the multiplexor.

Output Logic₃ MX₃ Output from Decrementor 0 Constant value 1

The SET Nx command loads N1-N4 with the following constants:

Index Constant Loaded Initial X[N] referred to N1 2 X[13] N2 7 X[8] N313 X[2] N4 15 X[0]

Note that each initial X[N_(n)] referred to matches the optimized SHA-1algorithm initial states for indexes N1-N4. When each index value N_(n)decrements, the effective X[N] increments. This is because the X wordsare stored in memory with most significant word first. The three VALunits are validation units connected to the Tamper Prevention andDetection circuitry, each with an OK bit. The OK bit is set to 1 onRESET, and ORed with the ChipOK values from both Tamper Detection Lineseach cycle. The OK bit is ANDed with each data bit that passes throughthe unit. All VAL units also parity check the data to ensure thecounters have not been tampered with. If a parity check fails, the EraseTamper Detection Line is triggered. In the case of VAL_(i), theeffective output from the counter Cl will always be 0 if the chip hasbeen tampered with. This prevents an attacker from executing any loopingconstructs that index through the keys. In the case of VAL₂, theeffective output from the counter C2 will always be 0 if the chip hasbeen tampered with. This prevents an attacker from executing any loopingconstructs. In the case of VAL₃, the effective output from any N counter(N1-N4) will always be 0 if the chip has been tampered with. Thisprevents an attacker from executing any looping constructs that indexthrough X.

Turning now to FIG. 203, there is illustrated 705 the information storedwithin the flash memory store 701. This data can include the following:

Factory Code

The factory code is a 16 bit code indicating the factory at which theprint roll was manufactured. This identifies factories belonging to theowner of the print roll technology, or factories making print rollsunder license. The purpose of this number is to allow the tracking offactory that a print roll came from, in case there are quality problems.

Batch Number

The batch number is a 32 bit number indicating the manufacturing batchof the print roll. The purpose of this number is to track the batch thata print roll came from, in case there are quality problems.

Serial Number

A 48 bit serial number is provided to allow unique identification ofeach print roll up to a maximum of 280 trillion print rolls.

Manufacturing Date

A 16 bit manufacturing date is included for tracking the age of printrolls, in case the shelf life is limited.

Media Length

The length of print media remaining on the roll is represented by thisnumber. This length is represented in small units such as millimeters orthe smallest dot pitch of printer devices using the print roll and toallow the calculation of the number of remaining photos in each of thewell known C, H, and P formats, as well as other formats which may beprinted. The use of small units also ensures a high resolution can beused to maintain synchronization with pre-printed media.

Media Type

The media type datum enumerates the media contained in the print roll.

(1) Transparent

(2) Opaque white

(3) Opaque tinted

(4) 3D lenticular

(5) Pre-printed: length specific

(6) Pre-printed: not length specific

(7) Metallic foil

(8) Holographic/optically variable device foil

Pre-Printed Media Length

The length of the repeat pattern of any pre-printed media contained, forexample on the back surface of the print roll is stored here.

Ink Viscosity

The viscosity of each ink color is included as an 8 bit number. the inkviscosity numbers can be used to adjust the print head actuatorcharacteristics to compensate for viscosity (typically, a higherviscosity will require a longer actuator pulse to achieve the same dropvolume).

Recommended Drop Volume for 1200 dpi

The recommended drop volume of each ink color is included as an 8 bitnumber. The most appropriate drop volume will be dependent upon the inkand print media characteristics. For example, the required drop volumewill decrease with increasing dye concentration or absorptivity. Also,transparent media require around twice the drop volume as opaque whitemedia, as light only passes through the dye layer once for transparentmedia.

As the print roll contains both ink and media, a custom match can beobtained. The drop volume is only the recommended drop volume, as theprinter may be other than 1200 dpi, or the printer may be adjusted forlighter or darker printing.

Ink Color

The color of each of the dye colors is included and can be used to “finetune” the digital half toning that is applied to any image beforeprinting.

Remaining Media Length Indicator

The length of print media remaining on the roll is represented by thisnumber and is updatable by the camera device. The length is representedin small units (e.g. 1200 dpi pixels) to allow calculation of the numberof remaining photos in each of C, H, and P formats, as well as otherformats which may be printed. The high resolution can also be used tomaintain synchronization with pre-printed media.

Copyright or Bit Pattern

This 512 bit pattern represents an ASCII character sequence sufficientto allow the contents of the flash memory store to be copyrightable.

Turning now to FIG. 204, there is illustrated the storage table 730 ofthe Artcam authorization chip. The table includes manufacturing code,batch number and serial number and date which have an identical formatto that previously described. The table 730 also includes information731 on the print engine within the Artcam device. The information storedcan include a print engine type, the DPI resolution of the printer and aprinter count of the number of prints produced by the printer device.

Further, an authentication test key 710 is provided which can randomlyvary from chip to chip and is utilised as the Artcam randomidentification code in the previously described algorithm. The 128 bitprint roll authentication key 713 is also provided and is equivalent tothe key stored within the print rolls. Next, the 512 bit pattern isstored followed by a 120 bit spare area suitable for Artcam use.

As noted previously, the Artcam preferably includes a liquid crystaldisplay 15 which indicates the number of prints left on the print rollstored within the Artcam. Further, the Artcam also includes a threestate switch 17 which allows a user to switch between three standardformats C H and P (classic, HDTV and panoramic). Upon switching betweenthe three states, the liquid crystal display 15 is updated to reflectthe number of images left on the print roll if the particular formatselected is used.

In order to correctly operate the liquid crystal display, the Artcamprocessor, upon the insertion of a print roll and the passing of theauthentication test reads the from the flash memory store of the printroll chip 53 and determines the amount of paper left. Next, the value ofthe output format selection switch 17 is determined by the Artcamprocessor. Dividing the print length by the corresponding length of theselected output format the Artcam processor determines the number ofpossible prints and updates the liquid crystal display 15 with thenumber of prints left. Upon a user changing the output format selectionswitch 17 the Artcam processor 31 re-calculates the number of outputpictures in accordance with that format and again updates the LCDdisplay 15.

The storage of process information in the printer roll table 705 (FIG.165) also allows the Artcam device to take advantage of changes inprocess and print characteristics of the print roll.

In particular, the pulse characteristics applied to each nozzle withinthe print head can be altered to take into account of changes in theprocess characteristics. Turning now to FIG. 205, the Artcam Processorcan be adapted to run a software program stored in an ancillary memoryROM chip. The software program, a pulse profile characteriser 771 isable to read a number of variables from the printer roll. Thesevariables include the remaining roll media on printer roll 772, theprinter media type 773, the ink color viscosity 774, the ink color dropvolume 775 and the ink color 776. Each of these variables are read bythe pulse profile characteriser and a corresponding, most suitable pulseprofile is determined in accordance with prior trial and experiment. Theparameters alters the printer pulse received by each printer nozzle soas to improve the stability of ink output.

It will be evident that the authorization chip includes significantadvances in that important and valuable information is stored on theprinter chip with the print roll. This information can include processcharacteristics of the print roll in question in addition to informationon the type of print roll and the amount of paper left in the printroll. Additionally, the print roll interface chip can provide valuableauthentication information and can be constructed in a tamper proofmanner. Further, a tamper resistant method of utilising the chip hasbeen provided. The utilization of the print roll chip also allows aconvenient and effective user interface to be provided for an immediateoutput form of Artcam device able to output multiple photographicformats whilst simultaneously able to provide an indicator of the numberof photographs left in the printing device.

Print Head Unit

Turning now to FIG. 206, there is illustrated an exploded perspectiveview, partly in section, of the print head unit 615 of FIG. 162.

The print head unit 615 is based around the print-head 44 which ejectsink drops on demand on to print media 611 so as to form an image. Theprint media 611 is pinched between two set of rollers comprising a firstset 618, 616 and second set 617, 619.

The print-head 44 operates under the control of power, ground and signallines 810 which provides power and control for the print-head 44 and arebonded by means of Tape Automated Bonding (TAB) to the surface of theprint-head 44.

Importantly, the print-head 44 which can be constructed from a siliconwafer device suitably separated, relies upon a series of anisotropicetches 812 through the wafer having near vertical side walls. Thethrough wafer etches 812 allow for the direct supply of ink to theprint-head surface from the back of the wafer for subsequent ejection.

The ink is supplied to the back of the inkjet print-head 44 by means ofink-head supply unit 814. The inkjet print-head 44 has three separaterows along its surface for the supply of separate colors of ink. Theink-head supply unit 814 also includes a lid 815 for the sealing of inkchannels.

In FIG. 207 to FIG. 210, there is illustrated various perspective viewsof the ink-head supply unit 814. Each of FIG. 207 to FIG. 210 illustrateonly a portion of the ink head supply unit which can be constructed ofindefinite length, the portions shown so as to provide exemplarydetails. In FIG. 207 there is illustrated a bottom perspective view,FIG. 148 illustrates a top perspective view, FIG. 209 illustrates aclose up bottom perspective view, partly in section, FIG. 210illustrates a top side perspective view showing details of the inkchannels, and FIG. 211 illustrates a top side perspective view as doesFIG. 212.

There is considerable cost advantage in forming ink-head supply unit 814from injection molded plastic instead of, say, micromachined silicon.The manufacturing cost of a plastic ink channel will be considerablyless in volume and manufacturing is substantially easier. The designillustrated in the accompanying Figures assumes a 1600 dpi three colormonolithic print head, of a predetermined length. The provided flow ratecalculations are for a 100 mm photo printer.

The ink-head supply unit 814 contains all of the required fine details.The lid 815 (FIG. 206) is permanently glued or ultrasonically welded tothe ink-head supply unit 814 and provides a seal for the ink channels.

Turning to FIG. 209, the cyan, magenta and yellow ink flows in throughink inlets 820-822, the magenta ink flows through the throughholes824,825 and along the magenta main channels 826,827 (FIG. 141). The cyanink flows along cyan main channel 830 and the yellow ink flows along theyellow main channel 831. As best seen from FIG. 209, the cyan ink in thecyan main channels then flows into a cyan sub-channel 833. The yellowsubchannel 834 similarly receiving yellow ink from the yellow mainchannel 831.

As best seen in FIG. 210, the magenta ink also flows from magenta mainchannels 826,827 through magenta throughholes 836, 837. Returning againto FIG. 209, the magenta ink flows out of the throughholes 836, 837. Themagenta ink flows along first magenta subchannel e.g. 838 and then alongsecond magenta subchannel e.g. 839 before flowing into a magenta trough840. The magenta ink then flows through magenta vias e.g. 842 which arealigned with corresponding inkjet head throughholes (e.g. 812 of FIG.166) wherein they subsequently supply ink to inkjet nozzles for printingout.

Similarly, the cyan ink within the cyan subchannel 833 flows into a cyanpit area 849 which supplies ink two cyan vias 843, 844. Similarly, theyellow subchannel 834 supplies yellow pit area 46 which in turn suppliesyellow vias 847, 848.

As seen in FIG. 210, the print-head is designed to be received withinprint-head slot 850 with the various vias e.g. 851 aligned withcorresponding through holes e.g. 851 in the print-head wafer.

Returning to FIG. 206, care must be taken to provide adequate ink flowto the entire print-head chip 44, while satisfying the constraints of aninjection moulding process. The size of the ink through wafer holes 812at the back of the print head chip is approximately 100 μm×50 μm, andthe spacing between through holes carrying different colors of ink isapproximately 170 μm. While features of this size can readily be moldedin plastic (compact discs have micron sized features), ideally the wallheight must not exceed a few times the wall thickness so as to maintainadequate stiffness. The preferred embodiment overcomes these problems byusing hierarchy of progressively smaller ink channels.

In FIG. 211, there is illustrated a small portion 870 of the surface ofthe print-head 44. The surface is divided into 3 series of nozzlescomprising the cyan series 871, the magenta series 872 and the yellowseries 873. Each series of nozzles is further divided into two rows e.g.875, 876 with the print-head 44 having a series of bond pads 878 forbonding of power and control signals.

The print head is preferably constructed in accordance with a largenumber of different forms of ink jet invented for uses including Artcamdevices. These ink jet devices are discussed in further detailhereinafter.

The print-head nozzles include the ink supply channels 880, equivalentto anisotropic etch hole 812 of FIG. 206. The ink flows from the back ofthe wafer through supply channel 881 and in turn through the filtergrill 882 to ink nozzle chambers e.g. 883. The operation of the nozzlechamber 883 and print-head 44 (FIG. 1) is, as mentioned previously,described in the abovementioned patent specification.

Ink Channel Fluid Flow Analysis

Turning now to an analysis of the ink flow, the main ink channels 826,827, 830, 831 (FIG. 207, FIG. 141) are around 1 mm×1 mm, and supply allof the nozzles of one color. The sub-channels 833, 834, 838, 839 (FIG.209) are around 200 μm×100 μm and supply about 25 inkjet nozzles each.The print head through holes 843, 844, 847, 848 and wafer through holese.g. 881 (FIG. 211) are 100 μm×50 μm and, supply 3 nozzles at each sideof the print head through holes. Each nozzle filter 882 has 8 slits,each with an area of 20 μm×2 μm and supplies a single nozzle.

An analysis has been conducted of the pressure requirements of an inkjet printer constructed as described. The analysis is for a 1,600 dpithree color process print head for photograph printing. The print widthwas 100 mm which gives 6,250 nozzles for each color, giving a total of18,750 nozzles.

The maximum ink flow rate required in various channels for full blackprinting is important. It determines the pressure drop along the inkchannels, and therefore whether the print head will stay filled by thesurface tension forces alone, or, if not, the ink pressure that isrequired to keep the print head full.

To calculate the pressure drop, a drop volume of 2.5 pl for 1,600 dpioperation was utilized. While the nozzles may be capable of operating ata higher rate, the chosen drop repetition rate is 5 kHz which issuitable to print a 150 mm long photograph in an little under 2 seconds.Thus, the print head, in the extreme case, has a 18,750 nozzles, allprinting a maximum of 5,000 drops per second. This ink flow isdistributed over the hierarchy of ink channels. Each ink channeleffectively supplies a fixed number of nozzles when all nozzles areprinting.

The pressure drop Δρ was calculated according to the Darcy-Weisbachformula:

${\Delta \; \rho} = \frac{\rho \; U^{2}{fL}}{2D}$

Where ρ is the density of the ink, U is the average flow velocity, L isthe length, D is the hydraulic diameter, and f is a dimensionlessfriction factor calculated as follows:

$f = \frac{k}{Re}$

Where Re is the Reynolds number and k is a dimensionless frictioncoefficient dependent upon the cross section of the channel calculatedas follows:

${Re} = \frac{UD}{v}$

Where ν is the kinematic viscosity of the ink.

For a rectangular cross section, k can be approximated by:

$k = \frac{64}{\frac{2}{3} + {\frac{11b\; 11b}{24a\; 24a}\left( {2 - {b/a}} \right)}}$

Where a is the longest side of the rectangular cross section, and b isthe shortest side. The hydraulic diameter D for a rectangular crosssection is given by:

$D = \frac{2{ab}}{a + b}$

Ink is drawn off the main ink channels at 250 points along the length ofthe channels. The ink velocity falls linearly from the start of thechannel to zero at the end of the channel, so the average flow velocityU is half of the maximum flow velocity. Therefore, the pressure dropalong the main ink channels is half of that calculated using the maximumflow velocity

Utilizing these formulas, the pressure drops can be calculated inaccordance with the following tables:

Table of Ink Channel Dimensions and Pressure Drops Max. ink # of Nozzlesflow at Pressure Items Length Width Depth supplied 5 KHz(U) drop ΔρCentral 1 106 mm  6.4 mm  1.4 mm 18,750  0.23 ml/s NA Moulding Cyan main1 100 mm  1 mm  1 mm 6,250  0.16 μl/μs  111 Pa channel (830) Magentamain 2 100 mm 700 μm 700 μm 3,125  0.16 μl/μs  231 Pa channel (826)Yellow main 1 100 mm  1 mm  1 mm 6,250  0.16 μl/μs  111 Pa channel (831)Cyan sub- 250  1.5 mm 200 μm 100 μm 25  0.16 μl/μs 41.7 Pa channel (833)Magenta sub- 500 200 μm  50 μm 100 μm 12.5 0.031 μl/μs 44.5 Pa channel(834)(a) Magenta sub- 500 400 μm 100 μm 200 μm 12.5 0.031 μl/μs  5.6 Pachannel (838)(b) Yellow sub- 250  1.5 mm 200 μm 100 μm 25 0.016 μl/μs41.7 Pa channel (834) Cyan pit (842) 250 200 μm 100 μm 300 μm 25 0.010μl/μs  3.2 Pa Magenta 500 200 μm  50 μm 200 μm 12.5 0.016 μl/μs 18.0 Pathrough (840) Yellow pit 250 200 μm 100 μm 300 μm 25 0.010 μl/μs  3.2 Pa(846) Cyan via (843) 500 100 μm  50 μm 100 μm 12.5 0.031 μl/μs 22.3 PaMagenta via 500 100 μm  50 μm 100 μm 12.5 0.031 μl/μs 22.3 Pa (842)Yellow via 500 100 μm  50 μm 100 μm 12.5 0.031 μl/μs 22.3 Pa Magenta 500200 μm 500 μm 100 μm 12.5 0.003 μl/μs 0.87 Pa through hole (837) Chipslot 1 100 mm 730 μm 625 18,750 NA NA Print head 1500 600μ 100 μm  50 μm12.5 0.052 μl/μs  133 Pa through holes (881)(in the chip substrate)Print head 1,000/  50 μm  60 μm  20 μm 3.125 0.049 μl/μs 62.8 Pa channelcolor segments (on chip front) Filter Slits (on 8 per  2 μm  2 μm  20 μm0.125 0.039 μl/μs  251 Pa entrance to nozzle nozzle chamber (882) Nozzlechamber 1 per  70 μm  30 μm  20 μm 1 0.021 μl/μs 75.4 Pa (on chip nozzlefront)(883)

The total pressure drop from the ink inlet to the nozzle is thereforeapproximately 701 Pa for cyan and yellow, and 845 Pa for magenta. Thisis less than 1% of atmospheric pressure. Of course, when the imageprinted is less than full black, the ink flow (and therefore thepressure drop) is reduced from these values.

Making the Mould for the Ink-Head Supply Unit

The ink head supply unit 14 (FIG. 1) has features as small as 50μ and alength of 106 mm. It is impractical to machine the injection mouldingtools in the conventional manner. However, even though the overall shapemay be complex, there are no complex curves required. The injectionmoulding tools can be made using conventional milling for the main inkchannels and other millimeter scale features, with a lithographicallyfabricated inset for the fine features. A LIGA process can be used forthe inset.

A single injection moulding tool could readily have 50 or more cavities.Most of the tool complexity is in the inset.

Turning to FIG. 206, the printing system is constructed via moulding inksupply unit 814 and lid 815 together and sealing them together aspreviously described. Subsequently print-head 44 is placed in itscorresponding slot 850. Adhesive sealing strips 852, 853 are placed overthe magenta main channels so to ensure they are properly sealed. TheTape Automated Bonding (TAB) strip 810 is then connected to the inkjetprint-head 44 with the tab bonding wires running in the cavity 855. Ascan best be seen from FIG. 206, FIG. 207 and FIG. 212, aperture slots855-862 are provided for the snap in insertion of rollers. The slotsprovided for the “clipping in” of the rollers with a small degree ofplay subsequently being provided for simple rotation of the rollers.

In FIG. 213 to FIG. 217, there are illustrated various perspective viewsof the internal portions of a finally assembled Artcam device withdevices appropriately numbered.

-   -   FIG. 213 illustrates a top side perspective view of the internal        portions of an Artcam camera, showing the parts flattened out;    -   FIG. 214 illustrates a bottom side perspective view of the        internal portions of an Artcam camera, showing the parts        flattened out; FIG. 215 illustrates a first    -   top side perspective view of the internal portions of an Artcam        camera, showing the parts as encased in an Artcam;

FIG. 216 illustrates a second top side perspective view of the internalportions of an Artcam camera, showing the parts as encased in an Artcam;

-   -   FIG. 217 illustrates a second top side perspective view of the        internal portions of an Artcam camera, showing the parts as        encased in an Artcam;

Postcard Print Rolls

Turning now to FIG. 218, in one form of the preferred embodiment, theoutput printer paper 11 can, on the side that is not to receive theprinted image, contain a number of pre-printed “postcard” formattedbacking portions 885. The postcard formatted sections 885 can includeprepaid postage “stamps” 886 which can comprise a printed authorizationfrom the relevant postage authority within whose jurisdiction the printroll is to be sold or utilised. By agreement with the relevantjurisdictional postal authority, the print rolls can be made availablehaving different postages. This is especially convenient where overseastravelers are in a local jurisdiction and wishing to send a number ofpostcards to their home country. Further, an address format portion 887is provided for the writing of address dispatch details in the usualform of a postcard. Finally, a message area 887 is provided for thewriting of a personalized information.

Turning now to FIG. 218 and FIG. 219, the operation of the camera deviceis such that when a series of images 890-892 is printed on a firstsurface of the print roll, the corresponding backing surface is thatillustrated in FIG. 218. Hence, as each image e.g. 891 is printed by thecamera, the back of the image has a ready made postcard 885 which can beimmediately dispatched at the nearest post office box within thejurisdiction. In this way, personalized postcards can be created.

It would be evident that when utilising the postcard system asillustrated in FIG. 219 and FIG. 220 only predetermined image sizes arepossible as the synchronization between the backing postcard portion 885and the front image 891 must be maintained. This can be achieved byutilising the memory portions of the authentication chip stored withinthe print roll to store details of the length of each postcard backingformat sheet 885. This can be achieved by either having each postcardthe same size or by storing each size within the print rolls on-boardprint chip memory.

The Artcam camera control system can ensure that, when utilising a printroll having pre-formatted postcards, that the printer roll is utilisedonly to print images such that each image will be on a postcardboundary. Of course, a degree of “play” can be provided by providingborder regions at the edges of each photograph which can account forslight misalignment.

Turning now to FIG. 220, it will be evident that postcard rolls can bepre-purchased by a camera user when traveling within a particularjurisdiction where they are available. The postcard roll can, on itsexternal surface, have printed information including country ofpurchase, the amount of postage on each postcard, the format of eachpostcard (for example being C, H or P or a combination of these imagemodes), the countries that it is suitable for use with and the postageexpiry date after which the postage is no longer guaranteed to besufficient can also be provided.

Hence, a user of the camera device can produce a postcard for dispatchin the mail by utilising their hand held camera to point at a relevantscene and taking a picture having the image on one surface and thepre-paid postcard details on the other. Subsequently, the postcard canbe addressed and a short message written on the postcard before itsimmediate dispatch in the mail.

In respect of the software operation of the Artcam device, although manydifferent software designs are possible, in one design, each Artcamdevice can consist of a set of loosely coupled functional modulesutilised in a coordinated way by a single embedded application to servethe core purpose of the device. While the functional modules are reusedin different combinations in various classes of Artcam device, theapplication is specific to the class of Artcam device.

Most functional modules contain both software and hardware components.The software is shielded from details of the hardware by a hardwareabstraction layer, while users of a module are shielded from itssoftware implementation by an abstract software interface. Because thesystem as a whole is driven by user-initiated and hardware-initiatedevents, most modules can run one or more asynchronous event-drivenprocesses.

The most important modules which comprise the generic Artcam device areshown in FIG. 221. In this and subsequent diagrams, software componentsare shown on the left separated by a vertical dashed line 901 fromhardware components on the right. The software aspects of these modulesare described below:

Software Modules—Artcam Application 902

The Artcam Application implements the high-level functionality of theArtcam device. This normally involves capturing an image, applying anartistic effect to the image, and then printing the image. In acamera-oriented Artcam device, the image is captured via the CameraManager 903. In a printer-oriented Artcam device, the image is capturedvia the Network Manager 904, perhaps as the result of the image being“squirted” by another device.

Artistic effects are found within the unified file system managed by theFile Manager 905. An artistic effect consist of a script file and a setof resources. The script is interpreted and applied to the image via theImage Processing Manager 906. Scripts are normally shipped on ArtCardsknown as Artcards. By default the application uses the script containedon the currently mounted Artcard. The image is printed via the PrinterManager 908.

When the Artcam device starts up, the bootstrap process starts thevarious manager processes before starting the application. This allowsthe application to immediately request services from the variousmanagers when it starts.

On initialization the application 902 registers itself as the handlerfor the events listed below. When it receives an event, it performs theaction described in the table.

User interface event Action Lock Focus Perform any automatic pre-capturesetup via the Camera Manager. This includes auto-focussing, auto-adjusting exposure, and charging the flash. This is normally initiatedby the user pressing the Take button halfway. Take Capture an image viathe Camera Manager. Self-Timer Capture an image in self-timed mode viathe Camera Manager. Flash Mode Update the Camera Manager to use the nextflash mode. Update the Status Display to show the new flash mode. PrintPrint the current image via the Printer Manager. Apply an artisticeffect to the image via the Image Processing Manager if there is acurrent script. Update the remaining prints count on the Status Display(see Print Roll Inserted below). Hold Apply an artistic effect to thecurrent image via the Image Processing Manager if there is a currentscript, but don't print the image. Eject ArtCards Eject the currentlyinserted ArtCards via the File Manager. Print Roll Calculate the numberof prints remaining based on Inserted the Print Manager's remainingmedia length and the Camera Manager's aspect ratio. Update the remainingprints count on the Status display. Print Roll Update the Status Displayto indicate there is no Removed print roll present.

Where the camera includes a display, the application also constructs agraphical user interface via the User Interface Manager 910 which allowsthe user to edit the current date and time, and other editable cameraparameters. The application saves all persistent parameters in flashmemory.

Real-Time Microkernel 911

The Real-Time Microkernel schedules processes preemptively on the basisof interrupts and process priority. It provides integrated inter-processcommunication and timer services, as these are closely tied to processscheduling. All other operating system functions are implemented outsidethe microkernel.

Camera Manager 903

The Camera Manager provides image capture services. It controls thecamera hardware embedded in the Artcam. It provides an abstract cameracontrol interface which allows camera parameters to be queried and set,and images captured. This abstract interface decouples the applicationfrom details of camera implementation. The Camera Manager utilizes thefollowing input/output parameters and commands:

output parameters domains focus range real, real zoom range real, realaperture range real, real shutter speed range real, real inputparameters domains focus real zoom real aperture real shutter speed realaspect ratio classic, HDTV, panoramic focus control mode multi-pointauto, single-point auto, manual exposure control mode auto, aperturepriority, shutter priority, manual flash mode auto, auto with red-eyeremoval, fill, off view scene mode on, off commands return value domainsLock Focus none Self-Timed Capture Raw Image Capture Image Raw Image

The Camera Manager runs as an asynchronous event-driven process. Itcontains a set of linked state machines, one for each asynchronousoperation. These include auto focussing, charging the flash, countingdown the self-timer, and capturing the image. On initialization theCamera Manager sets the camera hardware to a known state. This includessetting a normal focal distance and retracting the zoom. The softwarestructure of the Camera Manager is illustrated in FIG. 222. The softwarecomponents are described in the following subsections:

Lock Focus 913

Lock Focus automatically adjusts focus and exposure for the currentscene, and enables the flash if necessary, depending on the focuscontrol mode, exposure control mode and flash mode. Lock Focus isnormally initiated in response to the user pressing the Take buttonhalfway. It is part of the normal image capture sequence, but may beseparated in time from the actual capture of the image, if the userholds the take button halfway depressed. This allows the user to do spotfocusing and spot metering.

Capture Image 914

Capture Image captures an image of the current scene. It lights ared-eye lamp if the flash mode includes red-eye removal, controls theshutter, triggers the flash if enabled, and senses the image through theimage sensor. It determines the orientation of the camera, and hence thecaptured image, so that the image can be properly oriented during laterimage processing. It also determines the presence of camera motionduring image capture, to trigger deblurring during later imageprocessing.

Self-Timed Capture 915

Self-Timed Capture captures an image of the current scene after countingdown a 20 s timer. It gives the user feedback during the countdown viathe self-timer LED. During the first 15 s it can light the LED. Duringthe last 5 s it flashes the LED.

View Scene 917

View Scene periodically senses the current scene through the imagesensor and displays it on the color LCD, giving the user an LCD-basedviewfinder.

Auto Focus 918

Auto Focus changes the focal length until selected regions of the imageare sufficiently sharp to signify that they are in focus. It assumes theregions are in focus if an image sharpness metric derived from specifiedregions of the image sensor is above a fixed threshold. It finds theoptimal focal length by performing a gradient descent on the derivativeof sharpness by focal length, changing direction and stepsize asrequired. If the focus control mode is multi-point auto, then threeregions are used, arranged horizontally across the field of view. If thefocus control mode is single-point auto, then one region is used, in thecenter of the field of view. Auto Focus works within the available focallength range as indicated by the focus controller. In fixed-focusdevices it is therefore effectively disabled.

Auto Flash 919

Auto Flash determines if scene lighting is dim enough to require theflash. It assumes the lighting is dim enough if the scene lighting isbelow a fixed threshold. The scene lighting is obtained from thelighting sensor, which derives a lighting metric from a central regionof the image sensor. If the flash is required, then it charges theflash.

Auto Exposure 920

The combination of scene lighting, aperture, and shutter speed determinethe exposure of the captured image. The desired exposure is a fixedvalue. If the exposure control mode is auto, Auto Exposure determines acombined aperture and shutter speed which yields the desired exposurefor the given scene lighting. If the exposure control mode is aperturepriority, Auto Exposure determines a shutter speed which yields thedesired exposure for the given scene lighting and current aperture. Ifthe exposure control mode is shutter priority, Auto Exposure determinesan aperture which yields the desired exposure for the given scenelighting and current shutter speed. The scene lighting is obtained fromthe lighting sensor, which derives a lighting metric from a centralregion of the image sensor.

Auto Exposure works within the available aperture range and shutterspeed range as indicated by the aperture controller and shutter speedcontroller. The shutter speed controller and shutter controller hide theabsence of a mechanical shutter in most Artcam devices.

If the flash is enabled, either manually or by Auto Flash, then theeffective shutter speed is the duration of the flash, which is typicallyin the range 1/1000 s to 1/10000 s.

Image Processing Manager 906 (FIG. 221)

The Image Processing Manager provides image processing and artisticeffects services. It utilises the VLIW Vector Processor embedded in theArtcam to perform high-speed image processing. The Image ProcessingManager contains an interpreter for scripts written in the Vark imageprocessing language. An artistic effect therefore consists of a Varkscript file and related resources such as fonts, clip images etc. Thesoftware structure of the Image Processing Manager is illustrated inmore detail in FIG. 223 and include the following modules:

Convert and Enhance Image 921

The Image Processing Manager performs image processing in thedevice-independent CIE LAB color space, at a resolution which suits thereproduction capabilities of the Artcam printer hardware. The capturedimage is first enhanced by filtering out noise. It is optionallyprocessed to remove motion-induced blur. The image is then convertedfrom its device-dependent RGB color space to the CIE LAB color space. Itis also rotated to undo the effect of any camera rotation at the time ofimage capture, and scaled to the working image resolution. The image isfurther enhanced by scaling its dynamic range to the available dynamicrange.

Detect Faces 923

Faces are detected in the captured image based on hue and local featureanalysis. The list of detected face regions is used by the Vark scriptfor applying face-specific effects such as warping and positioningspeech balloons.

Vark Image Processing Language Interpreter 924

Vark consists of a general-purpose programming language with a rich setof image processing extensions. It provides a range of primitive datatypes (integer, real, boolean, character), a range of aggregate datatypes for constructing more complex types (array, string, record), arich set of arithmetic and relational operators, conditional anditerative control flow (if-then-else, while-do), and recursive functionsand procedures. It also provides a range of image-processing data types(image, clip image, matte, color, color lookup table, palette, dithermatrix, convolution kernel, etc.), graphics data types (font, text,path), a set of image-processing functions (color transformations,compositing, filtering, spatial transformations and warping,illumination, text setting and rendering), and a set of higher-levelartistic functions (tiling, painting and stroking).

A Vark program is portable in two senses. Because it is interpreted, itis independent of the CPU and image processing engines of its host.Because it uses a device-independent model space and adevice-independent color space, it is independent of the input colorcharacteristics and resolution of the host input device, and the outputcolor characteristics and resolution of the host output device.

The Vark Interpreter 924 parses the source statements which make up theVark script and produces a parse tree which represents the semantics ofthe script. Nodes in the parse tree correspond to statements,expressions, sub-expressions, variables and constants in the program.The root node corresponds to the main procedure statement list.

The interpreter executes the program by executing the root statement inthe parse tree. Each node of the parse tree asks its children toevaluate or execute themselves appropriately. An if statement node, forexample, has three children—a condition expression node, a thenstatement node, and an else statement node. The if statement asks thecondition expression node to evaluate itself, and depending on theboolean value returned asks the then statement or the else statement toexecute itself. It knows nothing about the actual condition expressionor the actual statements.

While operations on most data types are executed during execution of theparse tree, operations on image data types are deferred until afterexecution of the parse tree. This allows imaging operations to beoptimized so that only those intermediate pixels which contribute to thefinal image are computed. It also allows the final image to be computedin multiple passes by spatial subdivision, to reduce the amount ofmemory required.

During execution of the parse tree, each imaging function simply returnsan imaging graph—a graph whose nodes are imaging operators and whoseleaves are images—constructed with its corresponding imaging operator asthe root and its image parameters as the root's children. The imageparameters are of course themselves image graphs. Thus each successiveimaging function returns a deeper imaging graph.

After execution of the parse tree, an imaging graph is obtained whichcorresponds to the final image. This imaging graph is then executed in adepth-first manner (like any expression tree), with the following twooptimizations: (1) only those pixels which contribute to the final imageare computed at a given node, and (2) the children of a node areexecuted in the order which minimizes the amount of memory required. Theimaging operators in the imaging graph are executed in the optimizedorder to produce the final image. Compute-intensive imaging operatorsare accelerated using the VLIW Processor embedded in the Artcam device.If the amount of memory required to execute the imaging graph exceedsavailable memory, then the final image region is subdivided until therequired memory no longer exceeds available memory.

For a well-constructed Vark program the first optimization is unlikelyto provide much benefit per se. However, if the final image region issubdivided, then the optimization is likely to provide considerablebenefit. It is precisely this optimization, then, that allowssubdivision to be used as an effective technique for reducing memoryrequirements. One of the consequences of deferred execution of imagingoperations is that program control flow cannot depend on image content,since image content is not known during parse tree execution. Inpractice this is not a severe restriction, but nonetheless must be bornein mind during language design.

The notion of deferred execution (or lazy evaluation) of imagingoperations is described by Guibas and Stolfi (Guibas, L. J., and J.Stolfi, “A Language for Bitmap Manipulation”, ACM Transactions onGraphics, Vol. 1, No. 3, July 1982, pp. 191-214). They likewiseconstruct an imaging graph during the execution of a program, and duringsubsequent graph evaluation propagate the result region backwards toavoid computing pixels which do not contribute to the final image.Shantzis additionally propagates regions of available pixels forwardsduring imaging graph evaluation (Shantzis, M. A., “A Model for Efficientand Flexible Image Computing”, Computer Graphics Proceedings, AnnualConference Series, 1994, pp. 147-154). The Vark Interpreter uses themore sophisticated multi-pass bi-directional region propagation schemedescribed by Cameron (Cameron, S., “Efficient Bounds in ConstructiveSolid Geometry”, IEEE Computer Graphics & Applications, Vol. 11, No. 3,May 1991, pp. 68-74). The optimization of execution order to minimisememory usage is due to Shantzis, but is based on standard compilertheory (Aho, A. V., R. Sethi, and J. D. Ullman, “Generating Code fromDAGs”, in Compilers: Principles, Techniques, and Tools, Addison-Wesley,1986, pp. 557-567). The Vark Interpreter uses a more sophisticatedscheme than Shantzis, however, to support variable-sized image buffers.The subdivision of the result region in conjunction with regionpropagation to reduce memory usage is also due to Shantzis.

Printer Manager 908 (FIG. 221)

The Printer Manager provides image printing services. It controls theInk Jet printer hardware embedded in the Artcam. It provides an abstractprinter control interface which allows printer parameters to be queriedand set, and images printed. This abstract interface decouples theapplication from details of printer implementation and includes thefollowing variables:

output parameters domains media is present bool media has fixed pagesize bool media width real remaining media length real fixed page sizereal, real input parameters domains page size real, real commands returnvalue domains Print Image none output events invalid media mediaexhausted media inserted media removed

The Printer Manager runs as an asynchronous event-driven process. Itcontains a set of linked state machines, one for each asynchronousoperation. These include printing the image and auto mounting the printroll. The software structure of the Printer Manager is illustrated inFIG. 224. The software components are described in the followingdescription:

Print Image 930

Print Image prints the supplied image. It uses the VLIW Processor toprepare the image for printing. This includes converting the image colorspace to device-specific CMY and producing half-toned bi-level data inthe format expected by the print head.

Between prints, the paper is retracted to the lip of the print roll toallow print roll removal, and the nozzles can be capped to prevent inkleakage and drying. Before actual printing starts, therefore, thenozzles are uncapped and cleared, and the paper is advanced to the printhead. Printing itself consists of transferring line data from the VLIWprocessor, printing the line data, and advancing the paper, until theimage is completely printed. After printing is complete, the paper iscut with the guillotine and refracted to the print roll, and the nozzlesare capped. The remaining media length is then updated in the printroll.

Auto Mount Print Roll 131

Auto Mount Print Roll responds to the insertion and removal of the printroll. It generates print roll insertion and removal events which arehandled by the application and used to update the status display. Theprint roll is authenticated according to a protocol between theauthentication chip embedded in the print roll and the authenticationchip embedded in Artcam. If the print roll fails authentication then itis rejected. Various information is extracted from the print roll. Paperand ink characteristics are used during the printing process. Theremaining media length and the fixed page size of the media, if any, arepublished by the Print Manager and are used by the application.

User Interface Manager 910 (FIG. 221)

The User Interface Manager is illustrated in more detail if FIG. 225 andprovides user interface management services. It consists of a PhysicalUser Interface Manager 911, which controls status display and inputhardware, and a Graphical User Interface Manager 912, which manages avirtual graphical user interface on the color display. The UserInterface Manager translates virtual and physical inputs into events.Each event is placed in the event queue of the process registered forthat event.

File Manager 905 (FIG. 222)

The File Manager provides file management services. It provides aunified hierarchical file system within which the file systems of allmounted volumes appear. The primary removable storage medium used in theArtcam is the ArtCards. A ArtCards is printed at high resolution withblocks of bi-level dots which directly represents error-tolerantReed-Solomon-encoded binary data. The block structure supports appendand append-rewrite in suitable read-write ArtCards devices (notinitially used in Artcam). At a higher level a ArtCards can contain anextended append-rewriteable ISO9660 CD-ROM file system. The softwarestructure of the File Manager, and the ArtCards Device Controller inparticular, can be as illustrated in FIG. 226.

Network Manager 904 (FIG. 222)

The Network Manager provides “appliance” networking services acrossvarious interfaces including infra-red (IrDA) and universal serial bus(USB). This allows the Artcam to share captured images, and receiveimages for printing.

Clock Manager 907 (FIG. 222)

The Clock Manager provides date and time-of-day clock services. Itutilises the battery-backed real-time clock embedded in the Artcam, andcontrols it to the extent that it automatically adjusts for clock drift,based on auto-calibration carried out when the user sets the time.

Power Management

When the system is idle it enters a quiescent power state during whichonly periodic scanning for input events occurs. Input events include thepress of a button or the insertion of a ArtCards. As soon as an inputevent is detected the Artcam device re-enters an active power state. Thesystem then handles the input event in the usual way.

Even when the system is in an active power state, the hardwareassociated with individual modules is typically in a quiescent powerstate. This reduces overall power consumption, and allows particularlydraining hardware components such as the printer's paper cuttingguillotine to monopolise the power source when they are operating. Acamera-oriented Artcam device is, by default, in image capture mode.This means that the camera is active, and other modules, such as theprinter, are quiescent. This means that when non-camera functions areinitiated, the application must explicitly suspend the camera module.Other modules naturally suspend themselves when they become idle.

Watchdog Timer

The system generates a periodic high-priority watchdog timer interrupt.The interrupt handler resets the system if it concludes that the systemhas not progressed since the last interrupt, i.e. that it has crashed.

Alternative Print Roll

In an alternative embodiment, there is provided a modified form of printroll which can be constructed mostly from injection moulded plasticpieces suitably snapped fitted together. The modified form of print rollhas a high ink storage capacity in addition to a somewhat simplifiedconstruction. The print media onto which the image is to be printed iswrapped around a plastic sleeve former for simplified construction. Theink media reservoir has a series of air vents which are constructed soas to minimise the opportunities for the ink flow out of the air vents.Further, a rubber seal is provided for the ink outlet holes with therubber seal being pierced on insertion of the print roll into a camerasystem. Further, the print roll includes a print media ejection slot andthe ejection slot includes a surrounding moulded surface which providesand assists in the accurate positioning of the print media ejection slotrelative to the printhead within the printing or camera system.

Turning to FIG. 227 to FIG. 231, in FIG. 227 there is illustrated asingle point roll unit 1001 in an assembled form with a partial cutawayshowing internal portions of the printroll. FIG. 228 and FIG. 229illustrate left and right side exploded perspective views respectively.FIG. 230 and FIG. 231 are exploded perspective's of the internal coreportion 1007 of FIG. 227 to FIG. 229.

The print roll 1001 is constructed around the internal core portion 1007which contains an internal ink supply. Outside of the core portion 1007is provided a former 1008 around which is wrapped a paper or film supply1009. Around the paper supply it is constructed two cover pieces 1010,1011 which snap together around the print roll so as to form a coveringunit as illustrated in FIG. 227. The bottom cover piece 1011 includes aslot 1012 through which the output of the print media 1004 forinterconnection with the camera system.

Two pinch rollers 1038, 1039 are provided to pinch the paper against adrive pinch roller 1040 so they together provide for a decurling of thepaper around the roller 1040. The decurling acts to negate the strongcurl that may be imparted to the paper from being stored in the form ofprint roll for an extended period of time. The rollers 1038, 1039 areprovided to form a snap fit with end portions of the cover base portion1077 and the roller 1040 which includes a cogged end 1043 for driving,snap fits into the upper cover piece 1010 so as to pinch the paper 1004firmly between.

The cover pieces 1011 includes an end protuberance or lip 1042. The endlip 1042 is provided for accurately alignment of the exit hole of thepaper with a corresponding printing heat platen structure within thecamera system. In this way, accurate alignment or positioning of theexiting paper relative to an adjacent printhead is provided for fullguidance of the paper to the printhead.

Turning now to FIG. 230 and FIG. 231, there is illustrated explodedperspectives of the internal core portion which can be formed from aninjection moulded part and is based around 3 core ink cylinders havinginternal sponge portions 1034-1036.

At one end of the core portion there is provided a series of airbreathing channels e.g. 1014-1016. Each air breathing channel 1014-1016interconnects a first hole e.g. 1018 with an external contact point 1019which is interconnected to the ambient atmosphere. The path followed bythe air breathing channel e.g. 1014 is preferably of a winding nature,winding back and forth. The air breathing channel is sealed by a portionof sealing tape 1020 which is placed over the end of the core portion.The surface of the sealing tape 1020 is preferably hydrophobicallytreated to make it highly hydrophobic and to therefore resist the entryof any fluid portions into the air breathing channels.

At a second end of the core portion 1007 there is provided a rubbersealing cap 1023 which includes three thickened portions 1024, 1025 and1026 with each thickened portion having a series of thinned holes. Forexample, the portion 1024 has thinned holes 1029, 1030 and 1031. Thethinned holes are arranged such that one hole from each of the separatethickened portions is arranged in a single line. For example, thethinned holes 1031, 1032 and 1033 (FIG. 230) are all arranged in asingle line with each hole coming from a different thinned portion. Eachof the thickened portions corresponds to a corresponding ink supplyreservoir such that when the three holes are pierced, fluidcommunication is made with a corresponding reservoir.

An end cap unit 1044 is provided for attachment to the core portion1007. The end cap 1044 includes an aperture 1046 for the insertion of anauthentication chip 1033 in addition to a pronged adaptor (not shown)which includes three prongs which are inserted through correspondingholes (e.g., 1048), piercing a thinned portion (e.g., 1033) of seal 1023and interconnecting to a corresponding ink chamber (e.g., 1035).

Also inserted in the end portion 1044 is an authentication chip 1033,the authentication chip being provided to authenticate access of theprint roll to the camera system. This core portion is therefore dividedinto three separate chambers with each containing a separate color ofink and internal sponge. Each chamber includes an ink outlet in a firstend and an air breathing hole in the second end. A cover of the sealingtape 1020 is provided for covering the air breathing channels and therubber seal 1023 is provided for sealing the second end of the inkchamber.

The internal ink chamber sponges and the hydrophobic channel allow theprint roll to be utilized in a mobile environment and with manydifferent orientations. Further, the sponge can itself behydrophobically treated so as to force the ink out of the core portionin an orderly manner.

A series of ribs (e.g., 1027) can be provided on the surface of the coreportion so as to allow for minimal frictional contact between the coreportion 1007 and the printroll former 1008.

Most of the portions of the print roll can be constructed from ejectionmoulded plastic and the print roll includes a high internal ink storagecapacity. The simplified construction also includes a paper decurlingmechanism in addition to ink chamber air vents which provide for minimalleaking. The rubber seal provides for effective communication with anink supply chambers so as to provide for high operational capabilities.

Artcards can, of course, be used in many other environments. For exampleArtCards can be used in both embedded and personal computer (PC)applications, providing a user-friendly interface to large amounts ofdata or configuration information.

This leads to a large number of possible applications. For example, aArtCards reader can be attached to a PC. The applications for PCs aremany and varied. The simplest application is as a low cost read-onlydistribution medium. Since ArtCards are printed, they provide an audittrail if used for data distribution within a company.

Further, many times a PC is used as the basis for a closed system, yet anumber of configuration options may exist. Rather than rely on a complexoperating system interface for users, the simple insertion of a ArtCardsinto the ArtCards reader can provide all the configuration requirements.

While the back side of a ArtCards has the same visual appearanceregardless of the application (since it stores the data), the front of aArtCards is application dependent. It must make sense to the user in thecontext of the application.

It can therefore be seen that the arrangement provides for an efficientdistribution of information in the forms of books, newspapers,magazines, technical manuals, etc.

In a further application, the front side of a ArtCards 80 can show animage that includes an artistic effect to be applied to a sampled image.A camera system 81 can be provided which includes a cardreader 82 forreading the programmed data on the back of the card 80 and applying thealgorithmic data to a sampled image 83 so as to produce an output image84. The camera unit 81 including an on board inkjet printer andsufficient processing means for processing the sampled image data. Afurther application of the ArtCards concept, hereinafter called“BizCard” is to store company information on business cards. BizCard isa new concept in company information. The front side of a bizCard looksand functions exactly as today's normal business card. It includes aphotograph and contact information, with as many varied card styles asthere are business cards. However, the back of each bizCard contains aprinted array of black and white dots that holds 1-2 megabytes of dataabout the company. The result is similar to having the storage of a 3.5″disk attached to each business card.

The information could be company information, specific product sheets,web-site pointers, e-mail addresses, a resume . . . in short, whateverthe bizCard holder wants it to. BizCards can be read by any ArtCardsreader such as an attached PC card reader, which can be connected to astandard PC by a USB port. BizCards can also be displayed as documentson specific embedded devices. In the case of a PC, a user simply insertsthe bizCard into their reader. The bizCard is then preferably navigatedjust like a web-site using a regular web browser.

Simply by containing the owner's photograph and digital signature aswell as a pointer to the company's public key, each bizCard can be usedto electronically verify that the person is in fact who they claim to beand does actually work for the specified company. In addition bypointing to the company's public key, a bizCard permits simpleinitiation of secure communications.

A further application, hereinafter known as “TourCard” is an applicationof the ArtCards which contains information for tourists and visitors toa city. When a tourCard is inserted into the ArtCards book reader,information can be in the form of:

-   -   Maps    -   Public Transport Timetables    -   Places of Interest    -   Local history    -   Events and Exhibitions    -   Restaurant locations    -   Shopping Centres

TourCard is a low cost alternative to tourist brochures, guide books andstreet directories. With a manufacturing cost of just one cent per card,tourCards could be distributed at tourist information centres, hotelsand tourist attractions, at a minimum cost, or free if sponsored byadvertising. The portability of the bookreader makes it the perfectsolution for tourists. TourCards can also be used at informationkiosk's, where a computer equipped with the ArtCards reader can decodethe information encoded into the tourCard on any web browser.

It is interactivity of the bookreader that makes the tourCard soversatile. For example, Hypertext links contained on the map can beselected to show historical narratives of the feature buildings. In thisway the tourist can embark on a guided tour of the city, with relevanttransportation routes and timetables available at any time. The tourCardeliminates the need for separate maps, guide books, timetables andrestaurant guides and creates a simple solution for the independenttraveller.

Of course, many other utilizations of the data cards are possible. Forexample, newspapers, study guides, pop group cards, baseball cards,timetables, music data files, product parts, advertising, TV guides,movie guides, trade show information, tear off cards in magazines,recipes, classified ads, medical information, programmes and software,horse racing form guides, electronic forms, annual reports, restaurant,hotel and vacation guides, translation programmes, golf courseinformation, news broadcast, comics, weather details etc.

For example, the ArtCards could include a book's contents or anewspaper's contents. An example of such a system is as illustrated inFig. Z35 wherein the ArtCards 70 includes a book title on one surfacewith the second surface having the encoded contents of the book printedthereon. The card 70 is inserted in the reader 72 which can include aflexible display 73 which allows for the folding up of card reader 72.The card reader 72 can include display controls 74 which allow forpaging forward and back and other controls of the card reader 72.

1. A printing cartridge comprising: a roll of print media; a tubularformer around which the roll of print media is wound, the tubular formerbeing internally separated into two or more sections along alongitudinal axis of the tubular former and adapted to store supplies offluid therein; a casing comprising a pair of molded covers, the pair ofmolded covers being configured to releasably fasten together to encasethe roll of print media; and an ink collar for sealing an end of thetubular former, the ink collar defining two or more slits adapted toreceive therethrough fluid communication pins, whereby access to thesupplies of fluid in the tubular former is effected.
 2. A printingcartridge as claimed in claim 1, wherein the pair of molded coversdefine complementary formations to enable the molded covers to besnap-fitted together.
 3. A printing cartridge as claimed in claim 1,wherein at least one of the molded covers defines an elongate slotthrough which the print media exits the printing cartridge.
 4. Aprinting cartridge as claimed in claim 1, further comprising an end capfor sealing an end of the tubular former opposite to the end sealed bythe ink collar.
 5. A printing cartridge as claimed in claim 1, whereinthe slits are defined by a pair of elastomeric sealing curtains.
 6. Aprinting cartridge as claimed in claim 5, wherein the sealing curtainsare treated to have a hydrophobic characteristic.